From cc9c6086fef7c768d116ac51660dd14b9257f9f4 Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Mon, 8 Sep 2025 06:10:25 +0200 Subject: [PATCH] update book, typo in exercises week 38 --- .../_build/.doctrees/environment.pickle | Bin 305380 -> 305380 bytes .../_build/.doctrees/exercisesweek38.doctree | Bin 30573 -> 30573 bytes .../html/_sources/exercisesweek38.ipynb | 2 +- doc/LectureNotes/_build/html/chapter1.html | 2 +- doc/LectureNotes/_build/html/chapter10.html | 2 +- doc/LectureNotes/_build/html/chapter11.html | 2 +- doc/LectureNotes/_build/html/chapter12.html | 2 +- doc/LectureNotes/_build/html/chapter13.html | 2 +- doc/LectureNotes/_build/html/chapter2.html | 2 +- doc/LectureNotes/_build/html/chapter3.html | 2 +- doc/LectureNotes/_build/html/chapter4.html | 2 +- doc/LectureNotes/_build/html/chapter5.html | 2 +- doc/LectureNotes/_build/html/chapter6.html | 2 +- doc/LectureNotes/_build/html/chapter7.html | 2 +- doc/LectureNotes/_build/html/chapter8.html | 2 +- doc/LectureNotes/_build/html/chapter9.html | 2 +- .../_build/html/chapteroptimization.html | 2 +- doc/LectureNotes/_build/html/clustering.html | 2 +- .../_build/html/exercisesweek34.html | 2 +- .../_build/html/exercisesweek35.html | 2 +- .../_build/html/exercisesweek36.html | 2 +- .../_build/html/exercisesweek37.html | 2 +- .../_build/html/exercisesweek38.html | 10 +++++----- doc/LectureNotes/_build/html/genindex.html | 2 +- doc/LectureNotes/_build/html/intro.html | 2 +- doc/LectureNotes/_build/html/linalg.html | 2 +- doc/LectureNotes/_build/html/objects.inv | Bin 1021 -> 1022 bytes doc/LectureNotes/_build/html/project1.html | 6 +++--- doc/LectureNotes/_build/html/schedule.html | 2 +- doc/LectureNotes/_build/html/search.html | 2 +- doc/LectureNotes/_build/html/searchindex.js | 2 +- doc/LectureNotes/_build/html/statistics.html | 2 +- doc/LectureNotes/_build/html/teachers.html | 2 +- doc/LectureNotes/_build/html/textbooks.html | 2 +- doc/LectureNotes/_build/html/week34.html | 2 +- doc/LectureNotes/_build/html/week35.html | 2 +- doc/LectureNotes/_build/html/week36.html | 2 +- doc/LectureNotes/_build/html/week37.html | 6 +++--- .../jupyter_execute/exercisesweek38.ipynb | 2 +- 39 files changed, 44 insertions(+), 44 deletions(-) diff --git a/doc/LectureNotes/_build/.doctrees/environment.pickle b/doc/LectureNotes/_build/.doctrees/environment.pickle index f2aad6472dfbe6fd046551df7dda4b2ce9adb7ac..47056f27ef274f2c18436810a0d2ecfd84cf28fa 100644 GIT binary patch delta 11592 zcmZ8nd0)dD$Z`vCAT%b|Ut*vDFf_R_#kfkY`Cq>><{8d4h1mSQ|_2)RHo^ z_EM#&rQcS4TdGB?Ee&mbQOoa~bLU0!`{&N*EVG?+=FHqX_s$jjoh$aeNBXu1Oq`N9 zAt5O>F?Dic;^_JfbF)1OG|tWTN*EQNl9o83er~q6hV^2K;AoTeFO|{YjUrTb*J+fS z{r_49j$2ry?IyrYON>t#l{g`_NYnLzoiZWWk(iJM@c*@hbyA_m@QGs*b9-e6>#-%L zq$Q0_niijylsxWDUr^m6X*Q z&kXa&<{{AzUQ8V07C$wL)~fGjmo!g+(VwF*!0jKm?0-eM4cy#+i*g&fxi5-x8@ahJ zi*g&gxvz_In*g^WO`rr0+&zeo`2?&m zF}viD;mHZ(;>RWqNlPA*5}!6IcSdeC2ZoBHbOt`3ftsTXA`B2mS$tqjILaX^iI4L5 zz))~hK!omhR78X>cZ4EBH#@=*p=%xCh|rym2t?>XM1I_D*!3P@EQ6C>qjQk;ky+sC^&1GwTdfLD?tvtzcE?esl z(uqRrxorD)%^(Ub=(4HInM9!#UA9ws8APEaUA7Iq<`9L}blCzM&m#&g>arzXvnaHx z%T{q+CdpoA5NY&WKqQ*iWeYFkBnnOJvbFugqR`APTkg3ml7Xp#TJ5!nD73cA)?=te zp~YRcx<6PHTHR$^(_%4cqUBw-@slme&m#lLM@KCZUEs1+e_>JR2A6G9w zF5B#YRYakyT(-X|ttAR0-(_3>@w$O+%rXg`nB9y|7{Ol|X7und^OuAUEC?9kX4m1D zxD66PVr>pN^4-KR#?5_WgUyUYKmOD(7XhOrF^&V{xnW)e#{bMe62tkwhUq^djK46< z+EBcN$|J(erBHR|2!C_$*bp;sgdYpG>H_j4bPJF-q1S-y`Fl)MiaBufG3G_J>x}VZzJ$605+uDg=2!$8c1Esa zCKc5jv#|bhs~HB(1VWW?#>^}5^fw>D)5i=N7tVt6>y3kc1E|I6$$tEaVP+-QM9UmZ z{?WWUCCWUUGSj@65oPut?_y8Qf=Q9)uBSE4myttTnN-sZyiNRTHO}_L)&KE0>KoH&5zp zE(K!xKGxRkJ-M^lE-gxS{gQ>6w}1#pkCFlRST}Rcl+I>#7?9W0baO>Yl(}bmkbLRS z1I*8-#+rXlvKTo#MS$6HTCABpy@7dTT32(@L==RZU8cvHSJOy|H8D?4f7iS-9!8kJ zo0v)IvF5W`QRano)7%cdRb9lpn^$MVn)9Yc$(GxAMYG4uSTiy;N7Ql)Utgc+X6k9cwm*F4pZ4EzOd1VojgvQF2Fw zQPn!H_p?@Sqf24iTl`s)#5BH$X%wxHTe5!Ceti3Lb!nQt&85 zl!7NBq7*zA5vAZ9M3jQpA;NVY?bwNsQt%-}l!DJ7q7-};5vAZ;h#)E}%?pO8%x^R= ziphx6BFKz>=9NETeodn6`Fk>_Y1G{5&`4!1(`dlL8UkzC^X1}k7EkssD@rfhgw8(#ZZGSD;xo(L@ zUGh$76t>|bjc#sSp;6|CZd7MWHj@Xvd9qo3Te{5i;pOs=ZEMC51?7A17^6|<&KwKL zC4tPAUuSnMZmEpklciNW_PI1#zki`dEj|XzP*Z0Qz}yMFquhG84=vZc1)t2ekc^ln zJo3YiOwxkQM{T;JqsNzO-jI`ET55`aHbtX_r)OwX?sJV~Y+b{a|Iu09a(?W&om%C^ z`42VPcVUZ0qb`{m`CXo+(YhSSOC!YPw)^EnZ0v=CaT(PxiTm=6SJP3)S#pR%`00FI#T$hWoSfRx3GyAeFby zvrt*kLG*&O-&B4Q#5&5@%dnrqQdAY}tS&>+t_B7(FfGB~LfCcq3=E=0h$n%w;)8mV@OI6KC_8vnzNaaMa9U8_} zfteClhMyGW)a$p{Fir0~BTA_S)!1aM8d!sE)S@rH5H;0eJe6w5GjG z5vF?AWr>=8ktfQkpQ8)q80+RoXT4Q&41)zpgYs^`PHFgkL$+7Lb&b&!s9?VS)?DH&P?ys^&1obG1N-c75KQL5>5`Ztlq}tGcyhgDp}WZ^dAlp+pXiVS#E; zEUT(TD_XPH8g6aNAi7aYHEz!!5($3x4uiEua8$=a=-=7hqFNir&RYs**alxU_g!{H z>yPNhZfn@D2fJ=T3D8${?S(F&R(*OiNT%g;Su&mil4SBa9VY>OSqwu`k2<~|>uS;J zWPb*W9Yw0mK(r7+|G|au`VcmU$q{uR7~nLKA&=MBMv5QCnt(y;!z6bmumKvDO=KAw zZXdzQa7*FpC z99h|AjC1+bR^CW<&t;G0hHdU;Hefkx#n@}LdIgvU%C}ZRps?4n$2k_P)G7!oV8*Or zEjg4a>)0fufB67L0cH3G2rww~H$n_SIsZd;0!n$iFArAzwyOfnX!j0Vshbjhy^$|E|e*|bu5JMXT2DbcDXlKG?u%+ zVczO=KI?BWRrCRLI?C0FgSeOoMjyhILGZ$13^;=FQ`Ul8@a|EzOLI3JM@y5!(39w5 zf{#zJ9vb#O%~CBW$13inemcWOXi@*O?1_fM&f#hc?E^~$4!emmwx5os3tzJ4kpB8X zG?lx^;A}upUBawFu;*nqPs3lY;F2J2`ZYFE!+*ZUupsV=Zy0Pk1P@=wSRmN-1{mD`w}NMZKRER4(01TZ=r$)zk9r;UE>9xebN?dtU}Y@&vl z_i=3#_ug;Jn_G}Qz!Xc|RS$915sWQhTQz+4h^^Of=U=!JkV2Jzn7`G69MsqdQGNf% zqP1xCQwE15(klC$J++|hcY^!Mw^I#IRsRKZX!)L(Y`TUmUbCqdJaCr7GROLIeKVuJ z`hfHKnyxU#Xrx9P94t%i-|^t>^gNn*aoFba?m|ZJni?bf`0$RhMgy*|7dLugko zd^zl@pKMKbzpcD)UOp5g3tB!K-z8uNeP#EWr zr)v9U?5<8ODl?hs0T`k>!x{cJ_}yb0_5Lya7=yS+(nidT9-Ef?Y=xjZHwlx zNC0Zv^o!xJl#n*NKVryY1P$Tcz{*~8xDD+YRJpOjbPQLyIU3O8!~4SFgNrl z?CQf_;BVPK-tsGJB9HXuz2%8fZl^YUpO<4u+ttuMXlZ~U>hHd22IN})-Q1tUmO@%} z2l8VYLO>nS@Zu2uF~JbIuqyXfAH?$vX106^dwK$RF8o=rEVu|qujt{tGy^io{3x@e z8kxv@6D4OofPNa39=a)?dTQpN;6fiW*NIh7BCQr<}8zXSRCMBWBT@5xBYe!2Nj& zuZGHg)3^&uIi0s=a>zR(8Q%Ll$($MB{q?=A_e%9>21WpoAu2ipqXeK`U7UqhM<^ps z3STvQ4)18uTmL&3c21H!^cTSgGdbjcsxyBsNxk48D;plNnKZFWbC>!^sRtyZUn{Hb8LBZb)AiY_bRYCGP3H;2H}K z-OpiDBJS&azD>i!2XH3Dg?$y0FTsBgVQy+3VI;!`nMk?nQ}AR;q@i<(#}OU@8*Zcl z=ij4fN`e=Tao7g-)`op#zzIIU;>z9M@e1nalRQ{!d40z3YSEizT>1j5{0H+nad&*f$7@*o zI)~2y#D)0|)-d$HJdw$;a8^pm?-7zhz|F#Tm*3*anp^rdU$5a8KVh0D-Bouu97+h* zy@!!(b@2-(eu5qD^IaNx{LW8mc>NDtRHz^?jey0!|A5D>O`h!Y^w$_$fc7Va#*>lZJ1-z+6Tx{P7aEcZ8h{)DrSz7GV5WZh!Sa9p_<=`Eex_Vhb zm|DIuRKS6XxC6r7+=G<_Y?8!uMvBP%9kEiwa?t{E5OU=o-9>BV8RMR2k(INgesLykb!8ih_jMz)8o9?V zUkn#5)vzYwu_ZExZ<2Z(OYv5$748AvtZoDYH>p0IKaYdEs;5BWnJ~% z2zV{FG-+OgM&Wv(US1@LEn2h2>Xz!!XwhFw28|Vv(5d+)^No6{e6nb-=`st9x0Fl~ zkSeK>m*WeEx*}CT1|x3hM6pCe__TUJ*FF5P=%g-95v?`d`=E$aZKsJ=nm(&UxY|Em z^wM;fDlAHlI}GQpxEbPI&Aj=EsH3jW6rD6Z@`$LR2F)sz7aRroZ?gq#2sD9L*F>OP zeH_jj%jSxXnhD!wbyaG<=%MLdr$jxqJyW!`X!U9VE^Mm5>x`(P)@2EJ3$iBc!u&v@ z3tx!l>RNW;eEOe<`E*kqx0~I~$eWi%j2g35bkOpotD>5Eu&t;yo2%tJ-1_S2&cZ3=?S{dc8^24& z>yr8Ate^Dm{mx!dfdOfku=4C`{yrEIlFG;zn=Ax@0iQLI2O%-kLJ$lS2uTbB1z|AQ z5dzlwZPVP~>#vU*dCP5xZ+~?6HtZ+ZzDNaL*MsHSUm-Ti z-Vtq>8T}wcjk~KYsUF`GGm12|@K?xFG)T|i+*8f{-Q84Zb)%N*`2bu`Dv&+kH5g_D zIonfqt7Sx}DFqPvB>eJ`b}H>H3f`5pvrhaioR&)eC$K@Gvh;0WbXCKiY882|q0vf} zd=6=fnp*s?SZAS@FJYsj8W6ix)Nij~Lot8nw674|g!suX0 z|6>^AEY#c67-6A{He}1R5hP6dq(a zEVRb%ZaFx_h_`r|rQH2`mT~LNDQgU|q<@t&W?E=&1q0ryFj~ro8krW_A7((F@oois z8QeHdmU~;f_psq<9~*f>ZuvZ?{+7=qwb z*jY#m9NI!Xu3|X@a-!@<` zCHPmY0jDj3iERuxO(T@>r72S8w1DGQ`F0Q(mV8=!1NJhK!{=2m70|(eqaszE)6q!K z@PD0*(Hf@3fvYTqf-Vpv7EJA02%mH_;FJt4gs80*{?fGg7N|8euHc@WDtuaJ!nDRM>;xXb3~AhqYr0VXbk-cFp}I+1TV( z7!Tn|y7XyI!KXQQ-LKM&omxakGgyM|fx`zl?OE`SD5D-uEgap*>BeDQ3qH%WmYx&A zd-G-(aKfcI`(+q#dLVdhmXW4mzd5)zi2L{4LI_6{cQrVrxSb9Ml!ofM6P!*L_Hn^< zTOSujSM_m0bWa}_K$rA!-gHAB7f9FhaV6<)KF*Ua=Hqt5pxA1YCuHd0Dynly!c=-;LUvJd$r+fD}FS>LGA>O!y5U<;z8N6$cV|39DGQ4F6 z8Q!o%qjgQrqK{4uaG3xJP)RRIA z{)xzOJS`-V@~B_b7PexPcQMMh80BA#3M@ti6{CXRQ01Y+Qg2A0BHffsS!L9P{IhoHPw5%_7U;+ZaaUq)9kw4p}q>_@M;&Su}wx8o!f<@1)T? zaUFfQ&fwgJ_R7g_XUkXT4#xVG`B^@7A a)&BLyAy)Dl1L7(^F5}~CHEpBe@cci);yC#L delta 11592 zcmZWvd0)d1NCCVu^&%+Qk}5BX*KD_S%<-AWuk0VoM^izdW(jjf_30eJK?T zt+ln3s#^MO)we}!>EcW2;)_~-=bSt5k?-%HJD;=6+?jLEoS8dwZ(R(ybunP~q5e6g z6UM}+rYBBpS&&~gaZ2LEgru~@w8@EyW1B|)KTh+4e3yFTf_$%p3i3V8>jTQ?BqxoJPsVn2_u$q4 z)4gT|`5sB*(mRsBubadeXS0Y4C!S@vmt>2drwZ4GLPYc+EP# zruo{CpjlUkS^-Q?j87PoI1xJSesRPrjb>)6fpyI-1O2=s8YZPq9Y3PL9^hf#XdM(` z_wy)KD!;6|vo3Mz66~ffwwHNqVELS~DD=~H+_LA!Yusk88iB9tHg|E2*SRfRT%Xsu zkuL5(ueaM0xK(KYf4|OdnRpd_$bK9UQ+{42>+NN@-{l8eDe96Fa zzxvsd!BzPq!>l&AO3n*ZEKLq=IBsNt-4nazV}*h1J%YOGiZmDZDc1B(15b?1NKT~6 zFOgO5RaCiDOJM`vF1L}YKfNbCCvi&ph?JDEX~g8jq^NS+)b|z7ZBg%6Jolh%uXt{2 zGT>$8mm4-RC1HI0xWr-UDZ^6Z)5jEK7u2>thQ8V>Fcj=n@PY2PS4D&_w};>Z-E6Oh4|J_P6d&kLdl(}0puIYxa`>o$k1`&ma!T35 z5k5h2O++5}sD%&oq5Ta+&k((d=n$?GgAuL)#nU1I=r1f)6yRy(vDJNAa+sWke2|&1t*dDpj?P@+8YS zZJ$?|NEBMnX**gojVQFB(-!{1qR@&?+wy=6lA$G?wm(0fOcYwvY3sFoDp6=rr|nRK zX+)t_owl-nXAs2Ml%Jbw&{Ah7`pFh3d>XbwyCVSa>i0F@?G1jvif(L^6}_qZVQI&hww|49sG zfy56T<--g@Z2|cJ3NnX}@@D^-$)iH~--fwhR5e!4Y629>5V}6f2eZ~a5P1~)jPAzR zf6WC+Q_S;Yj<9FN3zAx}P>lBM0{e6r3{KfxDBn#N_8Cyd8X0Nk{G@5-;IT)TCpFkG z*@p>2ae$suW0#YUgrT|rr*OPq|^vo*Hf*Or37-o)K;ioZvM5vckLD{iL=c2 zr-#dHjahATTw07dDI?sxnr1hPCWp)XeyqCbNRKh|GsESXcou2a&xkR-GQ-W~8B@%T z>ESZ3fK4zrPKq%-r-jSRk5~t@@8lRWYht*J`+|j-*MYb_C0zR5VcpG@Q)0}*)Nr%( z)GRY#dbqhO(_cRK<$mU=snMoNvlxrF3qP~#v}p5EIx);c)8fn?Gc6pI8D~1CH8Z0! z{mk>3(PkZJIzNH8G?TKT&0*Q$=D94>tdSNj-(0|Zn3uAnP5(*Z^6f3Ws@ZdTwD~&_ zPq*?I^TqTS^9c-oY|aQXazeQIAg7=CWlp$h&s}70%?g+2JBvPM>WpYK?2IC_YfiY_ z7G^Xu*U#)p$;IB)6VeT(Nk|!Xdl$?WzQt|>sl#*8>qLjQ95v62>h*I)NM3j;* zBchc2BO*%4zayfQ{M-{JH|AtWfHrtgO0I;6Qu3RKC?z*TL@Bu)B1*||h$tlwLPRNf z3?fR&8Hgw)&q72gc`+hN$*U3JypOPNM@T9803u4sClOIfzJ!QU@^wTosjJTpgkUUg zF*}@@p-(CmPn=T^fq(Ibb2BaQmSe01_UD-dWEc~{#S`ZT3Q{awm}0R91dEDGKJYGX zx%h!qq1BQgPAWqS)>s_h!YJaHVZRu~!{>XaA$pPsU+`mXcfJQ;BSY*;36N>B}nX#vs~2;oEaOL_X*udP9b9 zB|r9OVCSb+w5lortPzalDZFEFAVVu7{4I!W)o^14c2L9AU={@9M}@-5tiQ$GUzKgp z^8F!fjD``ROmI1WD^H=-M4qh%))?kO%jQmg-D6n_$uEomvdyn?zy9 zMX-AL1{V)n)6n=-lU`uDVx`&DFI0QnXN?G+;3QsHrlh2vL0- zu|!QjFA^2i%?OuVLBKDwM9QlfJFejm&Dkyu*F>@d7F=@0P|2;>8YbsVWGS#bhRNlv z(W3KVO@{fep0;N7zzXwWhq7yKuvJcVHOU zprs-^F__K-KkLj)4aanKL*E!zi)vLYJ8LPJ)z*2dS?{uoT7Oh`_M?Uada^4PlmNX| zTyF+bn_l46mj!Zp{VYqtr9MeUU(n<6>(81nBz3Rj2e3GcR>udj6b;)C#xOxGEch7>CFwSL2KkylBz7ERh z0orGSma-`D#sKif_Ckyyf|1J@Bx8d6mg8I}*kL7u)d-;+r+69VT+Ie+(c?Aj4NIgV z)}bewdh2owm3#W(NyWo42v|wHDB8G<>>~L2{(Ji+5pf z_Ed#1fqmnAd8WR0Q|KPnn;{t>cNd6Ax$_%VMx7{T11+YC*oX0ea&>G!&NG6r9zfnC zc2HYr`#g`!L&~xgQ)wCy>JMkcm>0SxN%q6V9h=BJx&?o4!VY^oM43;2=7+`mt6i4 zBa*l?ZnA1z?k@wzhpoAkMP9s;I&uf+2S9)I;%7EV!#TgQ?i$|yjd^iW*nf}B)68Y} zS)qn)AFwSNK7NRKn%dg-Cri?>=HJZEYCsN-G|H>~|78(cwEQuHC6X#se9E3!Q1(B@ zePr7-!&5bV#_U@D;d6`}RFz@9jR5uTOI(7G-gk;a!X!!2TSharhVwa^t~|wvRAUVe zmZg{6^x&PWuBcX}c{VdY-kbtoCQW2NFW%L>aKK;f_Tq0bKmqERH-}{K)n?uTo$UH< zc~7p}!fUF@e!Kx=9%^G*J`76f|BMC7M$tS>we;t0k+ZI^2$bJf=hf8K0DcKMKYq#r z)uJFi4~gned7!FWfv-p6{t#YO{R&wS2sNV;Ukj!A<@%~BstSjU<<%ONAN+2@&mV>LfIgi*HC$3&=pH`wL16ZS}UA?qP0Gb<-N&aWudkb>+qu%G_S4qR_*F>*uGNJ)7wC$JM}rtpn>sL$KZ3#PyW>q`gLrK zt6#$#@n#I^Ahjg|OpQ?YYd{kY6ANkcog!a#ttp2s8lezt}OS= z<+F&9yaGcSH#B9{=tSPvBGvg(7>FoQea3J|Uj%`Z!S}Hr0$7p)EP1IAyL_U!*Pc=D>kAPBMP3L!kJe9%QBUxrLlJf7# z{2p*`PT{pt*=HJeVkt9uJ0=h0!v^47RyVmg8_l?Y2g;&t+*3Ww#xMZd-~4cHCDl2H zXIP{LgZpqK1YymE1W)jv1DLIbb%xKyu{ky5 z@=w5@Yx@d4Ej$kKFora2n-8NY37$K`Gc_D=45uP;<<9ST6?OAC57eU4pYhvT^lCy^ zIEiV1^l6sT)SY^Y_tBNEpN3(Y>%R*zBX;+KW21`l&KX!Pa(~ht>U9?K8IS?$>=)dZ z$>C?XdvgG%OWoztFJS-;&%%sg=dteq{Z*5%_yi62Ucl%gZp%xU0SO+xjI)bi>wn>h z2yXobCW-~?U*Rbl?)VPYA&Xn}-pWF+%m2vNX?Xf4eoVt< zw{QWaY7OsjSfB~+_?hQv*!fq!Q$yn}|5U?o|AVuMbaU^!J1HLUshYdsA!ZIzsPQK( zau&S&7v@0XWz#sfJs7HuX4uzUShD8*X$!8agpktz5*s3!3O;>FsN49fx=6D z*k8bonnXYkcwIDmkbrqiB99>gw%7#M3`K`f1Fy1Dui*lhWE|4Lc#J2K=e7`$YGH!A zN6$uzRhGycvaFH%ZWMe%TbeY?A!7ujVrt}BlGvm*>#lfPJsc|rYRQms0p7Dl~sRHsNHS&CdyVHef0v1=|hGd9E8XlP>VA@h!a0=8-ou4AwX}a%z zQA2f@CZaTbT8U7#CsXv+G@KHJ%kc+c+ZCHF-qp-&AB%?S%5>39)1wc;q0o?AxBS6j zkpDJA4ASx!mql5*;;5*vmdp}eH51mzI;#8}(NohqJ{67C*14jCMXML{#2A<8BG&a1kpZST9fs^Gk8 zscsd%d$rfp&_YqDxt`11X5747z%oIvh0o#g^1x8sjjnW!KI70h&qpKNt?Sg2ck~fPkBoC5fFNrtQy)Ca>v$a~f z&84p%Z+8!&XeV@**<}0~xO{Pa9cz72Zc&8+86aU!2B)p(VQzIU06?vw)5v9sKg=|GlE&NBUw$R(p#U!f+gm5kO+Y9j?GoLM`uQKaX zYhRKPXX&0{h7~=peR5?9ql+c|mtl;zP+w02c5SQY2C1)X23$3v^LvyrT)p)&bi7gW zh1Dle4e~K&T6(|x8XGONsjM;DLZSYK-9jq^TrHOmGKN{ax#eB&^{nX9n;Gnq{#nVG zZt2acV$88nken=goN}#jovIu47}5c1W(@=OzXZ$HG+;l2 zP{O3DtG+^h071Zx7 zjUo-#zGZCFaBv#~QWPn?c-w##j9^w<1J+f7e?}Xy86lY1-hka4Lb?4P!{7jWU*K zcyF}3&$E);jr)v+;InjBCA(q$@y1ro{W-<>z@;z&f|7J4d}VnnIHhyd{VLtqPNE75 zjyYW2tujUXvx0(6p7wznooO7@&D`?f?WAW0xNCN{0iQn9XP+DcHVgzW=Njo64w#Aa zfVh9nazogixT?X%#N}n!lQdUX9N=ZTyN?Z|i~HDWbZZ~$PgnM_eso_STZS&{W6RP_ zeQY_prjPZcJNj5Jx}b;Zcsma=yqX71yqAXp@8o04(}jF2r`vdF46ov$9^S(P^{6kF zzH|j2Tbl0QL5P>{AjF$@Xa=v{V;SAKgA6a+L57#@&?w%t$9AP__SklG#|{)66Z*|J ze0|_Zq^dLy=isgWV*9ctrAjS=zfmk|MG0z03F^ZV)F&mV!zHMrC8*;isLxy!{`<7p ze$qt}b*TjPbqVUn64cES)PoY#A0?>2N>Gp76#O2s*#6i}BIVKabz9g(j|lz#~-@D)`VUReGW2~-UiB~zChjo^rC?Q)|rr%)V%e|?rJ1qJ><0tNm(0tNm$ z0tNmz0tNmw0tNmt0tNmq0tNmn0tJR56c~z7U?@U?p$G;38v+IX7y<=`A`}>kP&}$? zmH0OZkQgRVU?@WIRQj(nf@)##0foT_1qL4!_>Tt^_=5)&aA3W0mC=m`pm8{87!DeRg9hQCF*s-l4jO@j2H>FnJE;2(>U|z{-a&nL(61~GnnMoicb;8D zLT?;2gB&!0@@W1zX!_*Q0P?8+4(h&xdhfuQvthNtxeYC}IKQKro6yN;Zh<`+NSr&* znIFX+s0XVV3m}~(!lUr>-0XVaqZP5w#Pz}WZ delta 32 qcmV+*0N?-Z?g8!Y0g#>nH<6zr0XMP2m}~(zlUr>-0XMUpZP5w#6%D}v diff --git a/doc/LectureNotes/_build/html/_sources/exercisesweek38.ipynb b/doc/LectureNotes/_build/html/_sources/exercisesweek38.ipynb index 355eef5c9..065cbdf95 100644 --- a/doc/LectureNotes/_build/html/_sources/exercisesweek38.ipynb +++ b/doc/LectureNotes/_build/html/_sources/exercisesweek38.ipynb @@ -5,7 +5,7 @@ "id": "1da77599", "metadata": {}, "source": [ - "# Exercises week 37\n", + "# Exercises week 38\n", "## September 15-19\n", "\n", "## Resampling and the Bias-Variance Trade-off" diff --git a/doc/LectureNotes/_build/html/chapter1.html b/doc/LectureNotes/_build/html/chapter1.html index e0cef45c9..8fca775a2 100644 --- a/doc/LectureNotes/_build/html/chapter1.html +++ b/doc/LectureNotes/_build/html/chapter1.html @@ -231,7 +231,7 @@
  • Week 36: Linear Regression and Gradient descent
  • Exercises week 37
  • Week 37: Gradient descent methods
    • -
  • Exercises week 37
    • +
  • Exercises week 38

    • Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

      diff --git a/doc/LectureNotes/_build/html/objects.inv b/doc/LectureNotes/_build/html/objects.inv index 84dbf9a8d0e39bfda697af52e238629e72faf478..dbaf85a89f92dec7d5946467a93969d71a0f48de 100644 GIT binary patch delta 858 zcmV-g1Eu`^2mS|;lz$<&v_L-wnhenPtk{dKVoRHq zv&x`40d3MnDie5r0*SYM$W2+m4Hw81++n6rYc569t{;b-j-A)XninY-88Em;OyOFp z9aAZM$6B$1{+OLqPaP^4-zRV{i>)PH^2bM1C=4gS)t{OfN?Jw(?6}F{60w3CN>tF+ z4tpBHo;vI&DYmkxEu=}PpO@|kXCcCwBivz9E1M7q=PkVV0#;j8OeML^d&_ax@aOKQ7&f{^)v$Y3PpDfZ2WZfbn>Od(5zk5WD z86`!n32m+YfSuJ3)ypnhG5eC^-}mxZvIGv6m^ng^Vv(WwYBe1tu(Ep zu{soKv;sJcTTZ53P(@SWASO+i8@Oe0KGj}6=Kf*TUU9HrVfH*(*) zkRS}YATmfrLp2D{+8q9&-C;qWbQQC&KDj-cjg(I#KW}Uu{bzKj1O4&;<%WJi6{VI< z>!eXVlJrK#n(9rux6GxnRxD{w!wpBzj}Q29pC9{&W2NW-jOudmyT^uniTlD>Yp kAk#$v+ttm!5GiV_%+aB!^tHs%W{U$qDE*W557K3N_cZvMeEHq zv&x`40d3NGDie5r0*SYM$W2+mEf>fX++(ItYc569t{;b-j-A)XninY-88Em(OyNeV zEmJ9c$6B$1{+O*)&mAfl-zV@Oi;X2+@uw$LC=4gS^`DvtF+ z4tpBHo;vI&DK@gGEu=}PpO@|kXCcCwBiv(BE1M7q=PkVV9F`kYOeML^d&6C3LeU(OGUG?Dr~qrlWhSZe;u=@L_Go7J2T^Dm%%i^nmX1MCftSv zqwp=nEP$9f#I?{^t_y6>J%<}5OKQ6Zf{^)<$Y3PpDR#|=Zfbn}LLp0pk5Wu516#YMs^W;?B{q_BOmpjO*yuHoJ4)8eS* ze_jT-myY{=*jTNHtPC&t-(~^=&i!S_S@tZGCcT96vFM7?T~f-nJpL}bIRaK>bk#Ip zWt0@PCbYHo19nzFRIj^im466bSEx2zlLU0ri7%+=-cfH6pU(yjI$H8q+#11J;p}`w zhz}FuFd-fhriTgBFkw0(%nlP~VZv-gf4DeIxHv?}kP4dOOXFIwH5S&nwK}h__TPxp zZOeXy#^81=DpC%*pettBYm3_Z8#hEm3PU~7=QzvYsaO;lt`(cW7h*J;ME$i;itQY= zl#0eA298qg-nR=b#GOoQ8cuhpO3B}(LW9SnwYlvp_XQ_Ff3e1= znE=hJO%P#8TDC?7Q+QYMRPZb}M-wSZ3jfK?A8C-HPI7EMdnvZI_8qE~rgbz{ zha!zu0EdyB&C9P_U$G1$ZD^pag6jdkv--9vNa%!Vgo*00W@}z>Lt>btRJ-Oz9$FU? zgh3ZX2B~PM1_4@|!#}n=EaXP@_FRvjjf~qjP`Y)KmNbm(9fx&)Us)v zG^$6E-pE)}y-D|$xinUaCCzEL;pqAC9zX8$WB+h06&-+4UG{$W*pP2L()&Wv*AEwD jIuBsGy4e>ZMQxQi+833+mN?pMzUK#}f3p4o&PjUq)|#Li diff --git a/doc/LectureNotes/_build/html/project1.html b/doc/LectureNotes/_build/html/project1.html index 57c5902c6..1caf6ce86 100644 --- a/doc/LectureNotes/_build/html/project1.html +++ b/doc/LectureNotes/_build/html/project1.html @@ -62,7 +62,7 @@ - + @@ -230,7 +230,7 @@
    • Week 36: Linear Regression and Gradient descent
    • Exercises week 37
    • Week 37: Gradient descent methods
      • -
    • Exercises week 37
      • +
    • Exercises week 38

    Projects

    Projects

    Projects

      diff --git a/doc/LectureNotes/_build/html/searchindex.js b/doc/LectureNotes/_build/html/searchindex.js index 95f0c0701..8a268d929 100644 --- a/doc/LectureNotes/_build/html/searchindex.js +++ b/doc/LectureNotes/_build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"1a)": [[18, "a"]], "3a)": [[18, "id1"]], "3b)": [[18, "b"]], "4a)": [[18, "id2"]], "4b)": [[18, "id3"]], "A Classification Tree": [[9, "a-classification-tree"]], "A Frequentist approach to data analysis": [[0, "a-frequentist-approach-to-data-analysis"], [27, "a-frequentist-approach-to-data-analysis"]], "A better approach": [[8, "a-better-approach"]], "A first summary": [[27, "a-first-summary"]], "A quick Reminder on Lagrangian Multipliers": [[8, "a-quick-reminder-on-lagrangian-multipliers"]], "A simple example": [[4, "a-simple-example"]], "A soft classifier": [[8, "a-soft-classifier"]], "A top-down perspective on Neural networks": [[1, "a-top-down-perspective-on-neural-networks"]], "ADAM algorithm, taken from Goodfellow et al": [[30, "adam-algorithm-taken-from-goodfellow-et-al"]], "ADAM optimizer": [[13, "adam-optimizer"], [30, "id2"]], "Accuracy": [[30, "accuracy"]], "Activation functions": [[12, "activation-functions"]], "AdaGrad Properties": [[30, "adagrad-properties"]], "AdaGrad Update Rule Derivation": [[30, "adagrad-update-rule-derivation"]], "AdaGrad algorithm, taken from Goodfellow et al": [[30, "adagrad-algorithm-taken-from-goodfellow-et-al"]], "Adam Optimizer": [[30, "adam-optimizer"]], "Adam vs. AdaGrad and RMSProp": [[30, "adam-vs-adagrad-and-rmsprop"]], "Adam: Bias Correction": [[30, "adam-bias-correction"]], "Adam: Exponential Moving Averages (Moments)": [[30, "adam-exponential-moving-averages-moments"]], "Adam: Update Rule Derivation": [[30, "adam-update-rule-derivation"]], "Adaptive boosting: AdaBoost, Basic Algorithm": [[10, "adaptive-boosting-adaboost-basic-algorithm"]], "Adaptivity Across Dimensions": [[30, "adaptivity-across-dimensions"]], "Adding error analysis and training set up": [[27, "adding-error-analysis-and-training-set-up"], [28, "adding-error-analysis-and-training-set-up"]], "Adjust hyperparameters": [[1, "adjust-hyperparameters"]], "Algorithms and codes for Adagrad, RMSprop and Adam": [[30, "algorithms-and-codes-for-adagrad-rmsprop-and-adam"]], "Algorithms for Setting up Decision Trees": [[9, "algorithms-for-setting-up-decision-trees"]], "An Overview of Ensemble Methods": [[10, "an-overview-of-ensemble-methods"]], "An extrapolation example": [[4, "an-extrapolation-example"]], "An optimization/minimization problem": [[27, "an-optimization-minimization-problem"]], "And finally \\boldsymbol{X}\\boldsymbol{X}^T": [[28, "and-finally-boldsymbol-x-boldsymbol-x-t"]], "And finally ADAM": [[30, "and-finally-adam"]], "And what about using neural networks?": [[27, "and-what-about-using-neural-networks"]], "Another Example, now with a polynomial fit": [[29, "another-example-now-with-a-polynomial-fit"]], "Another example, the moons again": [[9, "another-example-the-moons-again"]], "Applied Data Analysis and Machine Learning": [[20, null]], "Autocorrelation function": [[24, "autocorrelation-function"]], "Automatic differentiation": [[13, "automatic-differentiation"]], "Back to Ridge and LASSO Regression": [[28, "back-to-ridge-and-lasso-regression"], [29, "back-to-ridge-and-lasso-regression"]], "Back to the Cancer Data": [[11, "back-to-the-cancer-data"]], "Background literature": [[22, "background-literature"]], "Bagging": [[10, "bagging"]], "Bagging Examples": [[10, "bagging-examples"]], "Basic Matrix Features": [[21, "basic-matrix-features"]], "Basic ideas of the Principal Component Analysis (PCA)": [[11, null]], "Basic math of the SVD": [[5, "basic-math-of-the-svd"], [28, "basic-math-of-the-svd"], [29, "basic-math-of-the-svd"]], "Basics": [[7, "basics"]], "Basics of a tree": [[9, "basics-of-a-tree"]], "Batch Normalization": [[1, "batch-normalization"]], "Batches and mini-batches": [[30, "batches-and-mini-batches"]], "Bayes\u2019 Theorem and Ridge and Lasso Regression": [[5, "bayes-theorem-and-ridge-and-lasso-regression"]], "Boosting, a Bird\u2019s Eye View": [[10, "boosting-a-bird-s-eye-view"]], "Bootstrap": [[6, "bootstrap"]], "Bringing it together, first back propagation equation": [[12, "bringing-it-together-first-back-propagation-equation"]], "Building a Feed Forward Neural Network": [[1, null]], "Building a tree, regression": [[9, "building-a-tree-regression"]], "Building neural networks in Tensorflow and Keras": [[1, "building-neural-networks-in-tensorflow-and-keras"]], "But none of these can compete with Newton\u2019s method": [[30, "but-none-of-these-can-compete-with-newton-s-method"]], "CNNs in more detail, building convolutional neural networks in Tensorflow and Keras": [[3, "cnns-in-more-detail-building-convolutional-neural-networks-in-tensorflow-and-keras"]], "Cancer Data again now with Decision Trees and other Methods": [[9, "cancer-data-again-now-with-decision-trees-and-other-methods"]], "Challenge: Choosing a Fixed Learning Rate": [[30, "challenge-choosing-a-fixed-learning-rate"]], "Choose cost function and optimizer": [[1, "choose-cost-function-and-optimizer"]], "Classical PCA Theorem": [[11, "classical-pca-theorem"]], "Clustering and Unsupervised Learning": [[14, null]], "Code for SVD and Inversion of Matrices": [[5, "code-for-svd-and-inversion-of-matrices"]], "Code with a Number of Minibatches which varies": [[30, "code-with-a-number-of-minibatches-which-varies"]], "Codes and Approaches": [[14, "codes-and-approaches"]], "Codes for the SVD": [[5, "codes-for-the-svd"], [28, "codes-for-the-svd"], [29, "codes-for-the-svd"]], "Coding Setup and Linear Regression": [[15, "coding-setup-and-linear-regression"]], "Collect and pre-process data": [[1, "collect-and-pre-process-data"]], "Communication channels": [[27, "communication-channels"]], "Compare Bagging on Trees with Random Forests": [[10, "compare-bagging-on-trees-with-random-forests"]], "Comparing with a numerical scheme": [[2, "comparing-with-a-numerical-scheme"]], "Comparison with OLS": [[29, "comparison-with-ols"]], "Computation of gradients": [[30, "computation-of-gradients"]], "Computing the Gini index": [[9, "computing-the-gini-index"]], "Conditions on convex functions": [[29, "conditions-on-convex-functions"]], "Conjugate gradient method": [[13, "conjugate-gradient-method"]], "Convergence rates": [[30, "convergence-rates"]], "Convex function": [[29, "convex-function"]], "Convex functions": [[13, "convex-functions"], [29, "convex-functions"]], "Convolution Examples: Polynomial multiplication": [[3, "convolution-examples-polynomial-multiplication"]], "Convolution Examples: Principle of Superposition and Periodic Forces (Fourier Transforms)": [[3, "convolution-examples-principle-of-superposition-and-periodic-forces-fourier-transforms"]], "Convolutional Neural Network": [[12, "convolutional-neural-network"]], "Convolutional Neural Networks": [[3, null]], "Correlation Function and Design/Feature Matrix": [[28, "correlation-function-and-design-feature-matrix"]], "Correlation Matrix": [[11, "correlation-matrix"], [28, "correlation-matrix"]], "Correlation Matrix with Pandas": [[28, "correlation-matrix-with-pandas"]], "Course Format": [[27, "course-format"]], "Course setting": [[23, null]], "Covariance Matrix Examples": [[28, "covariance-matrix-examples"]], "Covariance and Correlation Matrix": [[28, "covariance-and-correlation-matrix"]], "Cross-validation": [[6, "cross-validation"]], "Deadlines for projects (tentative)": [[27, "deadlines-for-projects-tentative"]], "Decision trees, overarching aims": [[9, null]], "Deep learning methods": [[27, "deep-learning-methods"]], "Define model and architecture": [[1, "define-model-and-architecture"]], "Defining the cost function": [[1, "defining-the-cost-function"]], "Deliverables": [[15, "deliverables"], [16, "deliverables"]], "Derivation of the AdaGrad Algorithm": [[30, "derivation-of-the-adagrad-algorithm"]], "Derivatives and the chain rule": [[12, "derivatives-and-the-chain-rule"]], "Derivatives, example 1": [[28, "derivatives-example-1"]], "Deriving OLS from a probability distribution": [[5, "deriving-ols-from-a-probability-distribution"]], "Deriving and Implementing Ordinary Least Squares": [[16, "deriving-and-implementing-ordinary-least-squares"]], "Deriving and Implementing Ridge Regression": [[17, "deriving-and-implementing-ridge-regression"]], "Deriving the Lasso Regression Equations": [[28, "deriving-the-lasso-regression-equations"], [29, "deriving-the-lasso-regression-equations"], [29, "id6"]], "Deriving the Ridge Regression Equations": [[28, "deriving-the-ridge-regression-equations"], [29, "deriving-the-ridge-regression-equations"], [29, "id3"]], "Deriving the back propagation code for a multilayer perceptron model": [[12, "deriving-the-back-propagation-code-for-a-multilayer-perceptron-model"]], "Developing a code for doing neural networks with back propagation": [[1, "developing-a-code-for-doing-neural-networks-with-back-propagation"]], "Diagonalize the sample covariance matrix to obtain the principal components": [[11, "diagonalize-the-sample-covariance-matrix-to-obtain-the-principal-components"]], "Different kernels and Mercer\u2019s theorem": [[8, "different-kernels-and-mercer-s-theorem"]], "Disadvantages": [[9, "disadvantages"]], "Discriminative Modeling": [[27, "discriminative-modeling"]], "Domains and probabilities": [[24, "domains-and-probabilities"]], "Dropout": [[1, "dropout"]], "Economy-size SVD": [[28, "economy-size-svd"], [29, "economy-size-svd"]], "Elements of Probability Theory and Statistical Data Analysis": [[24, null]], "Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods": [[10, null]], "Entropy and the ID3 algorithm": [[9, "entropy-and-the-id3-algorithm"]], "Essential elements of ML": [[27, "essential-elements-of-ml"]], "Evaluate model performance on test data": [[1, "evaluate-model-performance-on-test-data"]], "Example 2": [[28, "example-2"]], "Example 3": [[28, "example-3"]], "Example 4": [[28, "example-4"]], "Example Matrix": [[28, "example-matrix"], [29, "example-matrix"]], "Example of discriminative modeling, taken from Generative Deep Learning by David Foster": [[27, "example-of-discriminative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of generative modeling, taken from Generative Deep Learning by David Foster": [[27, "example-of-generative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of own Standard scaling": [[28, "example-of-own-standard-scaling"]], "Example relevant for the exercises": [[28, "example-relevant-for-the-exercises"]], "Example: Exponential decay": [[2, "example-exponential-decay"]], "Example: Population growth": [[2, "example-population-growth"]], "Example: The diffusion equation": [[2, "example-the-diffusion-equation"]], "Example: binary classification problem": [[1, "example-binary-classification-problem"]], "Examples": [[27, "examples"]], "Examples of likelihood functions used in logistic regression and neural networks": [[7, "examples-of-likelihood-functions-used-in-logistic-regression-and-neural-networks"]], "Exercise 1 - Choice of model and degrees of freedom": [[17, "exercise-1-choice-of-model-and-degrees-of-freedom"]], "Exercise 1 - Finding the derivative of Matrix-Vector expressions": [[16, "exercise-1-finding-the-derivative-of-matrix-vector-expressions"]], "Exercise 1 - Github Setup": [[15, "exercise-1-github-setup"]], "Exercise 1, scale your data": [[18, "exercise-1-scale-your-data"]], "Exercise 1: Expectation values for ordinary least squares expressions": [[19, "exercise-1-expectation-values-for-ordinary-least-squares-expressions"]], "Exercise 1: Setting up various Python environments": [[0, "exercise-1-setting-up-various-python-environments"]], "Exercise 2 - Deriving the expression for OLS": [[16, "exercise-2-deriving-the-expression-for-ols"]], "Exercise 2 - Deriving the expression for Ridge Regression": [[17, "exercise-2-deriving-the-expression-for-ridge-regression"]], "Exercise 2 - Setting up a Github repository": [[15, "exercise-2-setting-up-a-github-repository"]], "Exercise 2, calculate the gradients": [[18, "exercise-2-calculate-the-gradients"]], "Exercise 2: Expectation values for Ridge regression": [[19, "exercise-2-expectation-values-for-ridge-regression"]], "Exercise 2: making your own data and exploring scikit-learn": [[0, "exercise-2-making-your-own-data-and-exploring-scikit-learn"]], "Exercise 3 - Creating feature matrix and implementing OLS using the analytical expression": [[16, "exercise-3-creating-feature-matrix-and-implementing-ols-using-the-analytical-expression"]], "Exercise 3 - Fitting an OLS model to data": [[15, "exercise-3-fitting-an-ols-model-to-data"]], "Exercise 3 - Scaling data": [[17, "exercise-3-scaling-data"]], "Exercise 3 - Setting up a Python virtual environment": [[15, "exercise-3-setting-up-a-python-virtual-environment"]], "Exercise 3, using the analytical formulae for OLS and Ridge regression to find the optimal paramters \\boldsymbol{\\theta}": [[18, "exercise-3-using-the-analytical-formulae-for-ols-and-ridge-regression-to-find-the-optimal-paramters-boldsymbol-theta"]], "Exercise 3: Deriving the expression for the Bias-Variance Trade-off": [[19, "exercise-3-deriving-the-expression-for-the-bias-variance-trade-off"]], "Exercise 3: Normalizing our data": [[0, "exercise-3-normalizing-our-data"]], "Exercise 4 - Fitting a polynomial": [[16, "exercise-4-fitting-a-polynomial"]], "Exercise 4 - Implementing Ridge Regression": [[17, "exercise-4-implementing-ridge-regression"]], "Exercise 4 - Testing multiple hyperparameters": [[17, "exercise-4-testing-multiple-hyperparameters"]], "Exercise 4 - The train-test split": [[15, "exercise-4-the-train-test-split"]], "Exercise 4, Implementing the simplest form for gradient descent": [[18, "exercise-4-implementing-the-simplest-form-for-gradient-descent"]], "Exercise 4: Adding Ridge Regression": [[0, "exercise-4-adding-ridge-regression"]], "Exercise 4: Computing the Bias and Variance": [[19, "exercise-4-computing-the-bias-and-variance"]], "Exercise 5 - Comparing your code with sklearn": [[16, "exercise-5-comparing-your-code-with-sklearn"]], "Exercise 5, Ridge regression and a new Synthetic Dataset": [[18, "exercise-5-ridge-regression-and-a-new-synthetic-dataset"]], "Exercise 5: Analytical exercises": [[0, "exercise-5-analytical-exercises"]], "Exercise: Cross-validation as resampling techniques, adding more complexity": [[6, "exercise-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Exercise: Analysis of real data": [[6, "exercise-analysis-of-real-data"]], "Exercise: Bias-variance trade-off and resampling techniques": [[6, "exercise-bias-variance-trade-off-and-resampling-techniques"]], "Exercise: Lasso Regression on the Franke function with resampling": [[6, "exercise-lasso-regression-on-the-franke-function-with-resampling"]], "Exercise: Ordinary Least Square (OLS) on the Franke function": [[6, "exercise-ordinary-least-square-ols-on-the-franke-function"]], "Exercise: Ridge Regression on the Franke function with resampling": [[6, "exercise-ridge-regression-on-the-franke-function-with-resampling"]], "Exercises": [[0, "exercises"]], "Exercises and Projects": [[6, "exercises-and-projects"]], "Exercises week 34": [[15, null]], "Exercises week 35": [[16, null]], "Exercises week 36": [[17, null]], "Exercises week 37": [[18, null], [19, null]], "Expectation values": [[24, "expectation-values"]], "Extending to more than one variable": [[29, "extending-to-more-than-one-variable"]], "Extremely useful tools, strongly recommended": [[27, "extremely-useful-tools-strongly-recommended"]], "Feed-forward neural networks": [[12, "feed-forward-neural-networks"]], "Feed-forward pass": [[1, "feed-forward-pass"]], "Final back propagating equation": [[12, "final-back-propagating-equation"]], "Fine-tuning neural network hyperparameters": [[1, "fine-tuning-neural-network-hyperparameters"]], "Fitting an Equation of State for Dense Nuclear Matter": [[0, "fitting-an-equation-of-state-for-dense-nuclear-matter"]], "Fixing the singularity": [[28, "fixing-the-singularity"], [29, "fixing-the-singularity"]], "Format for electronic delivery of report and programs": [[22, "format-for-electronic-delivery-of-report-and-programs"]], "Frequently used scaling functions": [[28, "frequently-used-scaling-functions"], [30, "frequently-used-scaling-functions"]], "From OLS to Ridge and Lasso": [[29, "from-ols-to-ridge-and-lasso"]], "From one to many layers, the universal approximation theorem": [[12, "from-one-to-many-layers-the-universal-approximation-theorem"]], "Functionality in Scikit-Learn": [[28, "functionality-in-scikit-learn"], [30, "functionality-in-scikit-learn"]], "Further Dimensionality Remarks": [[3, "further-dimensionality-remarks"]], "Further properties (important for our analyses later)": [[5, "further-properties-important-for-our-analyses-later"], [28, "further-properties-important-for-our-analyses-later"], [29, "further-properties-important-for-our-analyses-later"]], "Gaussian Elimination": [[21, "gaussian-elimination"]], "General Features": [[9, "general-features"]], "General linear models and linear algebra": [[27, "general-linear-models-and-linear-algebra"]], "Generalizing the fitting procedure as a linear algebra problem": [[27, "generalizing-the-fitting-procedure-as-a-linear-algebra-problem"], [27, "id1"]], "Generative Adversarial Networks": [[4, "generative-adversarial-networks"]], "Generative Models": [[4, "generative-models"]], "Generative Versus Discriminative Modeling": [[27, "generative-versus-discriminative-modeling"]], "Geometric Interpretation and link with Singular Value Decomposition": [[11, "geometric-interpretation-and-link-with-singular-value-decomposition"]], "Gradient Boosting, Classification Example": [[10, "gradient-boosting-classification-example"]], "Gradient Boosting, Examples of Regression": [[10, "gradient-boosting-examples-of-regression"]], "Gradient Clipping": [[1, "gradient-clipping"]], "Gradient Descent Example": [[29, "id1"], [30, "id1"]], "Gradient boosting: Basics with Steepest Descent/Functional Gradient Descent": [[10, "gradient-boosting-basics-with-steepest-descent-functional-gradient-descent"]], "Gradient descent": [[2, "gradient-descent"]], "Gradient descent and Ridge": [[29, "gradient-descent-and-ridge"], [30, "gradient-descent-and-ridge"]], "Gradient descent and revisiting Ordinary Least Squares from last week": [[30, "gradient-descent-and-revisiting-ordinary-least-squares-from-last-week"]], "Gradient descent example": [[29, "gradient-descent-example"], [30, "gradient-descent-example"]], "Grading": [[25, "grading"], [25, "id2"], [27, "grading"]], "How to take derivatives of Matrix-Vector expressions": [[16, "how-to-take-derivatives-of-matrix-vector-expressions"]], "Hyperplanes and all that": [[8, "hyperplanes-and-all-that"]], "Important Matrix and vector handling packages": [[21, "important-matrix-and-vector-handling-packages"]], "Important technicalities: More on Rescaling data": [[28, "important-technicalities-more-on-rescaling-data"]], "Improving gradient descent with momentum": [[30, "improving-gradient-descent-with-momentum"]], "Improving performance": [[1, "improving-performance"]], "In summary": [[25, "in-summary"]], "Including Stochastic Gradient Descent with Autograd": [[13, "including-stochastic-gradient-descent-with-autograd"], [30, "including-stochastic-gradient-descent-with-autograd"]], "Incremental PCA": [[11, "incremental-pca"]], "Installing R, C++, cython or Julia": [[27, "installing-r-c-cython-or-julia"]], "Installing R, C++, cython, Numba etc": [[27, "installing-r-c-cython-numba-etc"]], "Instructor information": [[25, "instructor-information"]], "Interpretations and optimizing our parameters": [[27, "interpretations-and-optimizing-our-parameters"], [27, "id2"], [27, "id3"], [28, "interpretations-and-optimizing-our-parameters"], [28, "id1"], [28, "id2"]], "Interpreting the Ridge results": [[28, "interpreting-the-ridge-results"], [29, "interpreting-the-ridge-results"], [29, "id4"]], "Introducing JAX": [[13, "introducing-jax"]], "Introducing the Covariance and Correlation functions": [[11, "introducing-the-covariance-and-correlation-functions"], [28, "introducing-the-covariance-and-correlation-functions"]], "Introduction": [[0, "introduction"], [6, "introduction"], [20, "introduction"], [21, "introduction"]], "Introduction to numerical projects": [[22, "introduction-to-numerical-projects"]], "Iterative Fitting, Classification and AdaBoost": [[10, "iterative-fitting-classification-and-adaboost"]], "Iterative Fitting, Regression and Squared-error Cost Function": [[10, "iterative-fitting-regression-and-squared-error-cost-function"]], "Kernel PCA": [[11, "kernel-pca"]], "Kernels and non-linearity": [[8, "kernels-and-non-linearity"]], "LU Decomposition, the inverse of a matrix": [[21, "lu-decomposition-the-inverse-of-a-matrix"]], "Lasso Regression": [[29, "lasso-regression"]], "Lasso case": [[29, "lasso-case"]], "Layers": [[1, "layers"]], "Layers used to build CNNs": [[3, "layers-used-to-build-cnns"]], "Learning goals": [[15, "learning-goals"], [16, "learning-goals"], [17, "learning-goals"], [18, "learning-goals"], [19, "learning-goals"]], "Learning outcomes": [[20, "learning-outcomes"], [27, "learning-outcomes"]], "Lectures and ComputerLab": [[27, "lectures-and-computerlab"]], "Limitations of supervised learning with deep networks": [[1, "limitations-of-supervised-learning-with-deep-networks"]], "Linear Algebra, Handling of Arrays and more Python Features": [[21, null]], "Linear Regression": [[0, null]], "Linear Regression Problems": [[28, "linear-regression-problems"], [29, "linear-regression-problems"]], "Linear Regression and the SVD": [[29, "linear-regression-and-the-svd"]], "Linear Regression, basic elements": [[0, "linear-regression-basic-elements"]], "Linking Bayes\u2019 Theorem with Ridge and Lasso Regression": [[5, "linking-bayes-theorem-with-ridge-and-lasso-regression"]], "Linking the regression analysis with a statistical interpretation": [[5, "linking-the-regression-analysis-with-a-statistical-interpretation"]], "Linking with the SVD": [[5, "linking-with-the-svd"], [28, "linking-with-the-svd"]], "Links to relevant courses at the University of Oslo": [[26, "links-to-relevant-courses-at-the-university-of-oslo"]], "Logistic Regression": [[7, null], [7, "id1"]], "MNIST and GANs": [[4, "mnist-and-gans"]], "Machine Learning": [[27, "machine-learning"]], "Machine learning": [[20, "machine-learning"]], "Main textbooks": [[27, "main-textbooks"]], "Making a tree": [[9, "making-a-tree"]], "Making your own Bootstrap: Changing the Level of the Decision Tree": [[10, "making-your-own-bootstrap-changing-the-level-of-the-decision-tree"]], "Making your own test-train splitting": [[28, "making-your-own-test-train-splitting"]], "Material for exercises week 35": [[28, "material-for-exercises-week-35"]], "Material for lab sessions sessions Tuesday and Wednesday": [[29, "material-for-lab-sessions-sessions-tuesday-and-wednesday"]], "Material for lecture Monday September 2": [[29, "material-for-lecture-monday-september-2"]], "Material for lecture Monday September 8": [[30, "material-for-lecture-monday-september-8"]], "Material for the lab sessions": [[30, "material-for-the-lab-sessions"]], "Mathematical Interpretation of Ordinary Least Squares": [[5, "mathematical-interpretation-of-ordinary-least-squares"], [28, "mathematical-interpretation-of-ordinary-least-squares"], [29, "mathematical-interpretation-of-ordinary-least-squares"]], "Mathematical optimization of convex functions": [[8, "mathematical-optimization-of-convex-functions"]], "Mathematics of CNNs": [[3, "mathematics-of-cnns"]], "Mathematics of the SVD and implications": [[5, "mathematics-of-the-svd-and-implications"], [28, "mathematics-of-the-svd-and-implications"], [29, "mathematics-of-the-svd-and-implications"]], "Matrices in Python": [[27, "matrices-in-python"]], "Matrix multiplication": [[1, "matrix-multiplication"]], "Matrix-vector notation and activation": [[12, "matrix-vector-notation-and-activation"]], "Meet the covariance!": [[24, "meet-the-covariance"]], "Meet the Covariance Matrix": [[5, "meet-the-covariance-matrix"], [28, "meet-the-covariance-matrix"]], "Meet the Hessian Matrix": [[28, "meet-the-hessian-matrix"]], "Meet the Pandas": [[27, "meet-the-pandas"]], "Min-Max Scaling": [[28, "min-max-scaling"]], "Momentum based GD": [[13, "momentum-based-gd"], [30, "momentum-based-gd"]], "More complicated Example: The Ising model": [[6, "more-complicated-example-the-ising-model"]], "More interpretations": [[28, "more-interpretations"], [29, "more-interpretations"], [29, "id5"]], "More on Dimensionalities": [[3, "more-on-dimensionalities"]], "More on Rescaling data": [[6, "more-on-rescaling-data"]], "More on Steepest descent": [[29, "more-on-steepest-descent"]], "More on convex functions": [[29, "more-on-convex-functions"]], "More preprocessing": [[28, "more-preprocessing"], [30, "more-preprocessing"]], "Motivation for Adaptive Step Sizes": [[30, "motivation-for-adaptive-step-sizes"]], "Multilayer perceptrons": [[12, "multilayer-perceptrons"]], "Network requirements": [[2, "network-requirements"]], "Neural Networks vs CNNs": [[3, "neural-networks-vs-cnns"]], "Neural networks": [[12, null]], "Note about SVD Calculations": [[28, "note-about-svd-calculations"], [29, "note-about-svd-calculations"]], "Note on Scikit-Learn": [[29, "note-on-scikit-learn"]], "Numerical experiments and the covariance, central limit theorem": [[24, "numerical-experiments-and-the-covariance-central-limit-theorem"]], "Numpy and arrays": [[21, "numpy-and-arrays"], [27, "numpy-and-arrays"]], "Numpy examples and Important Matrix and vector handling packages": [[27, "numpy-examples-and-important-matrix-and-vector-handling-packages"]], "Optimization and gradient descent, the central part of any Machine Learning algortithm": [[29, "optimization-and-gradient-descent-the-central-part-of-any-machine-learning-algortithm"]], "Optimization, the central part of any Machine Learning algortithm": [[13, null]], "Optimizing our parameters": [[27, "optimizing-our-parameters"]], "Optimizing our parameters, more details": [[27, "optimizing-our-parameters-more-details"]], "Optimizing the cost function": [[1, "optimizing-the-cost-function"]], "Organizing our data": [[0, "organizing-our-data"], [27, "organizing-our-data"]], "Other Matrix and Vector Operations": [[21, "other-matrix-and-vector-operations"]], "Other Types of Recurrent Neural Networks": [[4, "other-types-of-recurrent-neural-networks"]], "Other courses on Data science and Machine Learning at UiO": [[27, "other-courses-on-data-science-and-machine-learning-at-uio"]], "Other courses on Data science and Machine Learning at UiO, contn": [[27, "other-courses-on-data-science-and-machine-learning-at-uio-contn"]], "Other popular texts": [[27, "other-popular-texts"]], "Other techniques": [[11, "other-techniques"]], "Other types of networks": [[12, "other-types-of-networks"]], "Other ways of visualizing the trees": [[9, "other-ways-of-visualizing-the-trees"]], "Our model for the nuclear binding energies": [[27, "our-model-for-the-nuclear-binding-energies"]], "Overview of first week": [[27, "overview-of-first-week"]], "Overview video on Stochastic Gradient Descent (SGD)": [[30, "overview-video-on-stochastic-gradient-descent-sgd"]], "Own code for Ordinary Least Squares": [[27, "own-code-for-ordinary-least-squares"], [28, "own-code-for-ordinary-least-squares"]], "PCA and scikit-learn": [[11, "pca-and-scikit-learn"]], "Pandas AI": [[27, "pandas-ai"]], "Part a : Ordinary Least Square (OLS) for the Runge function": [[22, "part-a-ordinary-least-square-ols-for-the-runge-function"]], "Part b: Adding Ridge regression for the Runge function": [[22, "part-b-adding-ridge-regression-for-the-runge-function"]], "Part c: Writing your own gradient descent code": [[22, "part-c-writing-your-own-gradient-descent-code"]], "Part d: Including momentum and more advanced ways to update the learning the rate": [[22, "part-d-including-momentum-and-more-advanced-ways-to-update-the-learning-the-rate"]], "Part e: Writing our own code for Lasso regression": [[22, "part-e-writing-our-own-code-for-lasso-regression"]], "Part f: Stochastic gradient descent": [[22, "part-f-stochastic-gradient-descent"]], "Part g: Bias-variance trade-off and resampling techniques": [[22, "part-g-bias-variance-trade-off-and-resampling-techniques"]], "Part h): Cross-validation as resampling techniques, adding more complexity": [[22, "part-h-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Partial Differential Equations": [[2, "partial-differential-equations"]], "Plans for week 35": [[28, "plans-for-week-35"]], "Plans for week 36": [[29, "plans-for-week-36"]], "Plans for week 37, lecture Monday": [[30, "plans-for-week-37-lecture-monday"]], "Practical tips": [[13, "practical-tips"], [30, "practical-tips"]], "Practicalities": [[25, "practicalities"], [25, "id1"]], "Preamble: Note on writing reports, using reference material, AI and other tools": [[22, "preamble-note-on-writing-reports-using-reference-material-ai-and-other-tools"]], "Predicting New Points With A Trained Recurrent Neural Network": [[4, "predicting-new-points-with-a-trained-recurrent-neural-network"]], "Preprocessing our data": [[28, "preprocessing-our-data"]], "Prerequisites": [[27, "prerequisites"]], "Prerequisites and background": [[20, "prerequisites-and-background"]], "Prerequisites: Collect and pre-process data": [[3, "prerequisites-collect-and-pre-process-data"]], "Probability Distribution Functions": [[24, "probability-distribution-functions"]], "Program example for gradient descent with Ridge Regression": [[29, "program-example-for-gradient-descent-with-ridge-regression"], [30, "program-example-for-gradient-descent-with-ridge-regression"]], "Program for stochastic gradient": [[13, "program-for-stochastic-gradient"]], "Project 1 on Machine Learning, deadline October 6 (midnight), 2025": [[22, null]], "Properties of PDFs": [[24, "properties-of-pdfs"]], "Pros and cons": [[30, "pros-and-cons"]], "Pros and cons of trees, pros": [[9, "pros-and-cons-of-trees-pros"]], "Python installers": [[20, "python-installers"], [27, "python-installers"]], "RMS prop": [[13, "rms-prop"]], "RMSProp algorithm, taken from Goodfellow et al": [[30, "rmsprop-algorithm-taken-from-goodfellow-et-al"]], "RMSProp: Adaptive Learning Rates": [[30, "rmsprop-adaptive-learning-rates"]], "RMSprop for adaptive learning rate with Stochastic Gradient Descent": [[30, "rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent"]], "Random Numbers": [[24, "random-numbers"]], "Random forests": [[10, "random-forests"]], "Randomized PCA": [[11, "randomized-pca"]], "Reading material": [[27, "reading-material"]], "Reading recommendations:": [[28, "reading-recommendations"]], "Reading suggestions week 34": [[27, "reading-suggestions-week-34"]], "Readings and Videos:": [[30, "readings-and-videos"]], "Recurrent neural networks": [[12, "recurrent-neural-networks"]], "Recurrent neural networks: Overarching view": [[4, null]], "Reducing the number of degrees of freedom, overarching view": [[0, "reducing-the-number-of-degrees-of-freedom-overarching-view"], [28, "reducing-the-number-of-degrees-of-freedom-overarching-view"]], "Reformulating the problem": [[2, "reformulating-the-problem"]], "Regression Case": [[10, "regression-case"]], "Regression analysis and resampling methods": [[22, "regression-analysis-and-resampling-methods"]], "Regression analysis, overarching aims": [[27, "regression-analysis-overarching-aims"]], "Regression analysis, overarching aims II": [[27, "regression-analysis-overarching-aims-ii"]], "Regularization": [[1, "regularization"]], "Reminder from last week": [[28, "reminder-from-last-week"]], "Reminder on Newton-Raphson\u2019s method": [[29, "reminder-on-newton-raphson-s-method"]], "Reminder on Statistics": [[6, "reminder-on-statistics"]], "Reminder on different scaling methods": [[30, "reminder-on-different-scaling-methods"]], "Replace or not": [[13, "replace-or-not"], [30, "replace-or-not"]], "Required Technologies": [[20, "required-technologies"]], "Resampling Methods": [[6, null]], "Resampling and the Bias-Variance Trade-off": [[19, "resampling-and-the-bias-variance-trade-off"]], "Resampling methods": [[6, "id1"]], "Residual Error": [[28, "residual-error"], [29, "residual-error"]], "Resources on differential equations and deep learning": [[2, "resources-on-differential-equations-and-deep-learning"]], "Revisiting Ordinary Least Squares": [[29, "revisiting-ordinary-least-squares"]], "Revisiting our Linear Regression Solvers": [[13, "revisiting-our-linear-regression-solvers"]], "Rewriting the Covariance and/or Correlation Matrix": [[28, "rewriting-the-covariance-and-or-correlation-matrix"]], "Rewriting the fitting procedure as a linear algebra problem": [[27, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem"]], "Rewriting the fitting procedure as a linear algebra problem, more details": [[27, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem-more-details"]], "Ridge Regression": [[29, "ridge-regression"]], "Ridge and LASSO Regression": [[28, "ridge-and-lasso-regression"], [29, "ridge-and-lasso-regression"], [29, "id2"]], "Ridge and Lasso Regression": [[5, null], [5, "id1"]], "SGD example": [[30, "sgd-example"]], "SVD analysis": [[29, "svd-analysis"]], "Same code but now with momentum gradient descent": [[13, "same-code-but-now-with-momentum-gradient-descent"], [30, "same-code-but-now-with-momentum-gradient-descent"], [30, "id3"], [30, "id4"]], "Schedule first week": [[27, "schedule-first-week"]], "Schematic Regression Procedure": [[9, "schematic-regression-procedure"]], "Second moment of the gradient": [[30, "second-moment-of-the-gradient"]], "September 15-19": [[19, "september-15-19"]], "Setting up the Back propagation algorithm": [[12, "setting-up-the-back-propagation-algorithm"]], "Setting up the Matrix to be inverted": [[28, "setting-up-the-matrix-to-be-inverted"], [29, "setting-up-the-matrix-to-be-inverted"]], "Setting up the network using Autograd; The full program": [[2, "setting-up-the-network-using-autograd-the-full-program"]], "Similar (second order function now) problem but now with AdaGrad": [[13, "similar-second-order-function-now-problem-but-now-with-adagrad"], [30, "similar-second-order-function-now-problem-but-now-with-adagrad"]], "Simple Python Code to read in Data and perform Classification": [[9, "simple-python-code-to-read-in-data-and-perform-classification"]], "Simple case": [[28, "simple-case"], [29, "simple-case"]], "Simple code for solving the above problem": [[29, "simple-code-for-solving-the-above-problem"]], "Simple example code": [[30, "simple-example-code"]], "Simple example to illustrate Ordinary Least Squares, Ridge and Lasso Regression": [[29, "simple-example-to-illustrate-ordinary-least-squares-ridge-and-lasso-regression"]], "Simple geometric interpretation": [[29, "simple-geometric-interpretation"]], "Simple linear regression model using scikit-learn": [[0, "simple-linear-regression-model-using-scikit-learn"], [27, "simple-linear-regression-model-using-scikit-learn"]], "Simple one-dimensional second-order polynomial": [[18, "simple-one-dimensional-second-order-polynomial"]], "Simple program": [[29, "simple-program"], [30, "simple-program"]], "Slightly different approach": [[30, "slightly-different-approach"]], "Sneaking in automatic differentiation using Autograd": [[30, "sneaking-in-automatic-differentiation-using-autograd"]], "Software and needed installations": [[22, "software-and-needed-installations"], [27, "software-and-needed-installations"]], "Solving Differential Equations with Deep Learning": [[2, null]], "Solving the one dimensional Poisson equation": [[2, "solving-the-one-dimensional-poisson-equation"]], "Solving the wave equation with Neural Networks": [[2, "solving-the-wave-equation-with-neural-networks"]], "Some famous Matrices": [[21, "some-famous-matrices"]], "Some simple problems": [[13, "some-simple-problems"], [29, "some-simple-problems"]], "Some useful matrix and vector expressions": [[28, "some-useful-matrix-and-vector-expressions"]], "Splitting our Data in Training and Test data": [[0, "splitting-our-data-in-training-and-test-data"], [28, "splitting-our-data-in-training-and-test-data"]], "Standard steepest descent": [[13, "standard-steepest-descent"]], "Statistical analysis and optimization of data": [[20, "statistical-analysis-and-optimization-of-data"], [27, "statistical-analysis-and-optimization-of-data"]], "Steepest descent": [[13, "steepest-descent"], [29, "steepest-descent"]], "Stochastic Gradient Descent": [[30, "stochastic-gradient-descent"]], "Stochastic Gradient Descent (SGD)": [[13, "stochastic-gradient-descent-sgd"], [30, "stochastic-gradient-descent-sgd"]], "Stochastic variables and the main concepts, the discrete case": [[24, "stochastic-variables-and-the-main-concepts-the-discrete-case"]], "Support Vector Machines, overarching aims": [[8, null]], "Systematic reduction": [[3, "systematic-reduction"]], "Teachers": [[27, "teachers"]], "Teachers and Grading": [[25, null]], "Teaching Assistants Fall semester 2023": [[25, "teaching-assistants-fall-semester-2023"]], "Tentative deadllines for projects": [[25, "tentative-deadllines-for-projects"]], "Testing the Means Squared Error as function of Complexity": [[0, "testing-the-means-squared-error-as-function-of-complexity"], [28, "testing-the-means-squared-error-as-function-of-complexity"]], "Textbooks": [[26, null]], "The Algorithm before theorem": [[11, "the-algorithm-before-theorem"]], "The Breast Cancer Data, now with Keras": [[1, "the-breast-cancer-data-now-with-keras"]], "The CART algorithm for Classification": [[9, "the-cart-algorithm-for-classification"]], "The CART algorithm for Regression": [[9, "the-cart-algorithm-for-regression"]], "The CIFAR01 data set": [[3, "the-cifar01-data-set"]], "The Hessian matrix": [[29, "the-hessian-matrix"], [30, "the-hessian-matrix"]], "The Hessian matrix for Ridge Regression": [[29, "the-hessian-matrix-for-ridge-regression"], [30, "the-hessian-matrix-for-ridge-regression"]], "The Jacobian": [[28, "the-jacobian"]], "The MNIST dataset again": [[3, "the-mnist-dataset-again"]], "The OLS case": [[29, "the-ols-case"]], "The RELU function family": [[1, "the-relu-function-family"]], "The Ridge case": [[29, "the-ridge-case"]], "The SVD, a Fantastic Algorithm": [[28, "the-svd-a-fantastic-algorithm"], [29, "the-svd-a-fantastic-algorithm"]], "The Softmax function": [[1, "the-softmax-function"]], "The \\chi^2 function": [[0, "the-chi-2-function"], [27, "the-chi-2-function"], [27, "id4"], [27, "id5"], [27, "id6"], [27, "id7"], [27, "id8"]], "The bias-variance tradeoff": [[6, "the-bias-variance-tradeoff"]], "The code for solving the ODE": [[2, "the-code-for-solving-the-ode"]], "The complete code with a simple data set": [[28, "the-complete-code-with-a-simple-data-set"]], "The cost/loss function": [[28, "the-cost-loss-function"]], "The course has two central parts": [[20, "the-course-has-two-central-parts"]], "The derivative of the cost/loss function": [[29, "the-derivative-of-the-cost-loss-function"], [30, "the-derivative-of-the-cost-loss-function"]], "The equations": [[29, "the-equations"]], "The equations for ordinary least squares": [[28, "the-equations-for-ordinary-least-squares"]], "The first Case": [[29, "the-first-case"]], "The gradient step": [[30, "the-gradient-step"]], "The ideal": [[29, "the-ideal"]], "The logistic function": [[7, "the-logistic-function"]], "The mean squared error and its derivative": [[28, "the-mean-squared-error-and-its-derivative"]], "The moons example": [[8, "the-moons-example"]], "The multilayer perceptron (MLP)": [[12, "the-multilayer-perceptron-mlp"]], "The network with one input layer, specified number of hidden layers, and one output layer": [[2, "the-network-with-one-input-layer-specified-number-of-hidden-layers-and-one-output-layer"]], "The plethora of machine learning algorithms/methods": [[27, "the-plethora-of-machine-learning-algorithms-methods"]], "The sensitiveness of the gradient descent": [[29, "the-sensitiveness-of-the-gradient-descent"]], "The singular value decomposition": [[5, "the-singular-value-decomposition"], [28, "the-singular-value-decomposition"], [29, "the-singular-value-decomposition"]], "The two-dimensional case": [[8, "the-two-dimensional-case"]], "Time decay rate": [[30, "time-decay-rate"]], "To our real data: nuclear binding energies. Brief reminder on masses and binding energies": [[27, "to-our-real-data-nuclear-binding-energies-brief-reminder-on-masses-and-binding-energies"]], "Topics covered in this course: Statistical analysis and optimization of data": [[27, "topics-covered-in-this-course-statistical-analysis-and-optimization-of-data"]], "Towards the PCA theorem": [[11, "towards-the-pca-theorem"]], "Train and test datasets": [[1, "train-and-test-datasets"]], "Two-dimensional Objects": [[3, "two-dimensional-objects"]], "Type of problem": [[2, "type-of-problem"]], "Types of Machine Learning": [[27, "types-of-machine-learning"]], "Useful Python libraries": [[20, "useful-python-libraries"], [27, "useful-python-libraries"]], "Using Autograd": [[13, "using-autograd"]], "Using forward Euler to solve the ODE": [[2, "using-forward-euler-to-solve-the-ode"]], "Using gradient descent methods, limitations": [[13, "using-gradient-descent-methods-limitations"], [29, "using-gradient-descent-methods-limitations"], [30, "using-gradient-descent-methods-limitations"]], "Visualization": [[1, "visualization"], [1, "id1"]], "Visualizing the Tree, Classification": [[9, "visualizing-the-tree-classification"]], "Week 34: Introduction to the course, Logistics and Practicalities": [[27, null]], "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression": [[28, null]], "Week 36: Linear Regression and Gradient descent": [[29, null]], "Week 37: Gradient descent methods": [[30, null]], "What Is Generative Modeling?": [[27, "what-is-generative-modeling"]], "What does it mean?": [[28, "what-does-it-mean"], [29, "what-does-it-mean"]], "What is Machine Learning?": [[0, "what-is-machine-learning"]], "What is a good model?": [[0, "what-is-a-good-model"], [27, "what-is-a-good-model"]], "What is a good model? Can we define it?": [[27, "what-is-a-good-model-can-we-define-it"]], "When do we stop?": [[30, "when-do-we-stop"]], "Which activation function should I use?": [[1, "which-activation-function-should-i-use"]], "Why Combine Momentum and RMSProp?": [[30, "why-combine-momentum-and-rmsprop"]], "Why Linear Regression (aka Ordinary Least Squares and family)": [[27, "why-linear-regression-aka-ordinary-least-squares-and-family"]], "Wisconsin Cancer Data": [[7, "wisconsin-cancer-data"]], "With Lasso Regression": [[29, "with-lasso-regression"]], "Writing Our First Generative Adversarial Network": [[4, "writing-our-first-generative-adversarial-network"]], "Writing our own PCA code": [[11, "writing-our-own-pca-code"]], "Writing the Cost Function": [[29, "writing-the-cost-function"]], "XGBoost: Extreme Gradient Boosting": [[10, "xgboost-extreme-gradient-boosting"]], "Yet another Example": [[29, "yet-another-example"]], "a) Expression for Ridge regression": [[17, "a-expression-for-ridge-regression"]], "scikit-learn implementation": [[1, "scikit-learn-implementation"]]}, "docnames": ["chapter1", "chapter10", "chapter11", "chapter12", "chapter13", "chapter2", "chapter3", "chapter4", "chapter5", "chapter6", "chapter7", "chapter8", "chapter9", "chapteroptimization", "clustering", "exercisesweek34", "exercisesweek35", "exercisesweek36", "exercisesweek37", "exercisesweek38", "intro", "linalg", "project1", "schedule", "statistics", "teachers", "textbooks", "week34", "week35", "week36", "week37"], "envversion": {"sphinx": 62, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1}, "filenames": ["chapter1.ipynb", "chapter10.ipynb", "chapter11.ipynb", "chapter12.ipynb", "chapter13.ipynb", "chapter2.ipynb", "chapter3.ipynb", "chapter4.ipynb", "chapter5.ipynb", "chapter6.ipynb", "chapter7.ipynb", "chapter8.ipynb", "chapter9.ipynb", "chapteroptimization.ipynb", "clustering.ipynb", "exercisesweek34.ipynb", "exercisesweek35.ipynb", "exercisesweek36.ipynb", "exercisesweek37.ipynb", "exercisesweek38.ipynb", "intro.md", "linalg.ipynb", "project1.ipynb", "schedule.md", "statistics.ipynb", "teachers.md", "textbooks.md", "week34.ipynb", "week35.ipynb", "week36.ipynb", "week37.ipynb"], "indexentries": {}, "objects": {}, "objnames": {}, "objtypes": {}, "terms": {"": [0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 19, 20, 21, 22, 24, 25, 27, 28], "0": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 25, 27, 28, 29, 30], "00": [0, 1, 5, 11, 27, 28], "000": [1, 3], "00000000e": [], "001": [2, 8, 13, 29, 30], "004": 5, "004113634617443131": 28, "004113634617443139": 28, "00411363461744314": 28, "004113634617443147": 28, "00727646693": [0, 27], "0086649156": [0, 27], "01": [0, 1, 2, 5, 9, 11, 13, 17, 26, 27, 28, 30], "0110": 24, "01719003e": [], "02": [0, 4, 7, 12, 27], "02334824": [], "02857": 4, "02f": 6, "03077640549": 4, "03097597e": [], "031": 5, "04": 11, "0458": 9, "05": [4, 6], "062292565": 4, "062435": [], "06730814": [], "07": [], "0713": [0, 27], "07285": 3, "08": 24, "08078025e": [], "08336233266": 4, "08376632": 28, "083766322923899": 28, "0837663229239043": 28, "0917": 9, "0n": [0, 27], "0x113e21950": 17, "1": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 23, 24, 25, 26, 27, 29, 30], "10": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 23, 24, 25, 27, 28, 29, 30], "100": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 24, 25, 27, 28, 29, 30], "1000": [0, 1, 2, 4, 5, 8, 11, 13, 14, 18, 19, 20, 24, 27, 29, 30], "10000": [2, 5, 6, 10, 11, 13, 24], "100000": 8, "10001": 10, "1001": 24, "1002": 24, "1003": 24, "1005": 24, "1009": 24, "101": 16, "1011": 24, "1013": 24, "1013904243": 24, "1015": 24, "102": 16, "1023": 24, "1024": 3, "1026": 24, "1027": 24, "103": 1, "1030": 24, "1037": 24, "1038": 24, "1040": 24, "1047": 24, "107": 16, "108": [], "10th": 9, "10x": [0, 27], "11": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 21, 22, 24, 26, 27, 28, 29, 30], "110": [], "1100": 24, "1101": 24, "111": [1, 7, 12], "112": 16, "11340253": [], "11590451": [], "116": 16, "117": 16, "118": 16, "12": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 18, 21, 24, 26, 27, 28, 29, 30], "120": 3, "121": [8, 9, 10, 16], "1215pm": [25, 27], "122": [8, 9, 10], "124": [0, 27], "125": 16, "127": [4, 16], "128": [3, 4, 13, 30], "129": 16, "1298": 9, "12pm": [25, 27], "13": [0, 2, 9, 12, 21, 24, 27], "131": 16, "133": 7, "135": 16, "136": 16, "14": [0, 2, 4, 6, 8, 9, 10, 12, 21, 24, 26, 28], "141": 16, "1412": 30, "143": 16, "1446729567": 4, "149": 16, "14g": 6, "15": [0, 2, 4, 6, 7, 8, 9, 12, 13, 22, 24, 27, 29, 30], "150": [4, 8], "152": 16, "153760": [], "156": 16, "157": [], "158": [], "159": 16, "15g": 6, "15pm": 27, "16": [1, 2, 3, 4, 5, 8, 9, 10, 24, 27, 29], "160": 16, "1603": 3, "161": 16, "162": 16, "16231451": 4, "163": 16, "16384": 3, "164": 16, "167": 16, "17": [1, 2, 8, 24], "172": 16, "173": 16, "176": 16, "178": 16, "179": 16, "1797": 1, "18": [2, 6, 7, 8, 9, 10, 24, 27], "1807": 4, "18392847": [], "19": [2, 24, 27], "1940": [], "1943": 12, "19569961": 28, "1970": [21, 27], "1973": 9, "1979": 6, "1_1": 12, "1_2": 12, "1_3": 12, "1cm": [0, 8, 10, 24, 27], "1d": [1, 2, 3], "1e": [2, 4, 13, 14, 30], "1e10": 14, "1e4": 6, "1f": 1, "1k": 21, "1n": [0, 27], "1x": [0, 27], "2": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 24, 26, 30], "20": [0, 1, 2, 6, 7, 8, 16, 17, 24, 25, 27, 28, 29, 30], "200": [0, 2, 3, 4, 8, 9, 10], "2000": [0, 28], "2004": [13, 29], "2006": 26, "20072279": [], "2008": 27, "2010": 1, "2011": 1, "2012": 30, "2014": [4, 30], "2015": 1, "2016": [0, 27], "2018": [0, 6, 28], "2021": [6, 14, 28, 30], "2022": 27, "2025": [18, 27, 28, 29, 30], "21": [0, 1, 5, 7, 9, 12, 21, 27, 28, 29], "2116753732": 4, "215pm": [25, 27], "2167072": [], "22": [0, 1, 5, 12, 13, 21, 27, 28, 29], "221": 8, "225": 4, "22948497": [], "23": [1, 12, 21], "24": [0, 1, 21, 27], "25": [2, 3, 4, 5, 6, 8, 9, 11, 28], "250": [2, 4, 7, 9], "25000": [], "250154": [], "253775": [], "255": 3, "256": 4, "25x": 22, "26": [], "26303845": [], "264": [], "265": [], "265109911": 4, "266": [], "269": [], "27": 1, "270": [], "278": [29, 30], "27n_": 24, "28": [1, 3, 4], "283": [29, 30], "2830637392": 4, "2861": 24, "2873": 9, "2882": 24, "2886": 24, "2890": [0, 27], "2892": 24, "29": 28, "2915": 24, "2931": 27, "29364655": [], "294399745619595": [], "296247": [], "2968": 27, "2980": 27, "298273": [], "298375": [], "2990": 27, "2_": 12, "2_1": 12, "2_2": 12, "2_3": 12, "2_i": 12, "2_m": [6, 24], "2_t": 13, "2_x": 24, "2a": 17, "2b": 24, "2c8f433990d1": 30, "2cm": 8, "2d": [1, 3, 11, 12, 20, 27], "2e": 6, "2f": [0, 7, 9, 10, 11, 12, 27], "2g": 2, "2g_i": 2, "2k": 3, "2m": 6, "2mvizaqfst8": 28, "2n": [0, 2, 3, 27, 28], "2nd": 9, "2p": 24, "2pt": 4, "2x": [0, 3, 8, 13, 27], "2x_ix_jy_iy_j": 8, "2x_j": 8, "2y_i": 10, "2y_j": 8, "3": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 23, 24, 25, 27, 29, 30], "30": [0, 1, 4, 6, 7, 10, 13, 25, 30], "30000": [0, 27], "3072": 3, "31": [12, 21, 24], "315": [6, 28, 30], "3155": [0, 5, 6, 28, 29, 30], "32": [3, 4, 6, 12, 13, 21, 24, 30], "3200": 1, "3250": 1, "3297": [], "33": [12, 21, 25], "3303": [], "3310": [], "332331": [], "333": 7, "3331": [], "3337": [], "34": 21, "3436": [0, 27], "3437": [0, 27], "35": [0, 6, 22, 27, 29, 30], "3581341341": 4, "359": [5, 29], "36": [0, 5, 6, 18, 22, 24], "37": [22, 29], "370782966": 4, "38": [22, 24], "39": [0, 25, 27], "3d": [2, 3, 4, 6, 13, 16], "3f": [1, 3, 9], "3n": 21, "3x": [2, 8], "3x_i": 2, "3y": 8, "4": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 24, 27, 29, 30], "40": [1, 6, 25, 27], "400": 4, "4000": 27, "4050": [26, 27], "41": 21, "4155": [2, 15], "41589548": [], "42": [1, 4, 8, 9, 10, 21], "43": [0, 7, 21], "4310": 27, "436462435": 4, "44": [0, 21, 29, 30], "45": [25, 27], "46": [25, 27], "462": 7, "47": [25, 27], "479465113": 4, "47958494": [], "48": [], "48257387": [25, 27], "49": [5, 6, 11], "49152": 3, "4940954": [0, 27], "4990": 24, "4992": 24, "4997": 24, "4c4c7f": [9, 10], "4d": 3, "4f": 6, "4pm": [25, 27], "4y": 8, "4y_i": 10, "5": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 22, 24, 27, 28, 29, 30], "50": [1, 2, 3, 4, 6, 7, 8, 10, 13, 27, 28, 30], "500": [1, 3, 4, 6, 9, 10, 13, 30], "5018": 24, "506": [], "507d50": [9, 10], "50j": 13, "50x10": 1, "51": 10, "510": 1, "512132": [], "5177783846": 4, "53": 9, "54": [6, 24], "5411205": [], "54894451": [], "55": 1, "56": 1, "56536": [0, 27], "569": 1, "57": [0, 8, 25, 27], "571": [5, 29], "58": [10, 25, 27], "591317992": 4, "5cm": 24, "5f": [8, 30], "5x": [8, 18], "5y": 8, "6": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 18, 21, 24, 25, 27, 28, 29, 30], "60": [1, 3], "60000": 4, "6019067271": 4, "606439": [], "625": 7, "63": 1, "64": [1, 3, 4, 13, 21, 27, 30], "64x50": 1, "65": [1, 8, 9], "6887363571": 4, "69": [16, 24], "69069n_": 24, "691": [], "6980": 30, "6n_": 24, "7": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 21, 22, 24, 26, 27, 28, 30], "70": [1, 7], "70653767": 4, "71": 1, "724": 3, "73": [], "7304881": [], "75": [5, 6, 8, 11], "76": [25, 27], "765": 7, "77": [25, 27], "7718": 9, "7782028952": 4, "77893972": [], "78": [], "7d7d58": [9, 10], "8": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 21, 24, 25, 27, 29], "80": [0, 1, 5, 8, 17, 28], "800": [4, 7], "81": 1, "815am": [25, 27], "85": 1, "8702784034": 4, "88": 27, "8f": 6, "8g": 6, "8n": 21, "8x8": 1, "9": [0, 1, 2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 21, 24, 27, 30], "90": 1, "9040": 9, "91": [25, 27], "92": [25, 27], "93": 16, "931": [0, 27], "933": [5, 29], "937": 24, "938": 24, "939": [0, 24, 27], "94": 24, "95": [1, 11], "954": 24, "955820c21e8b": 4, "96": 6, "960": 24, "961": 24, "962": 24, "9649652536": 4, "96611194e": [], "9780387310732": 26, "9780387848570": 26, "9781098134174": 27, "9781492032632": 26, "9781801819312": 27, "97898392": 28, "98": [0, 1, 16], "985": 24, "986": 24, "989": 24, "9898ff": [9, 10], "99": [13, 16, 30], "991": 24, "992": 24, "993": 24, "996": 5, "999": [9, 24, 30], "9x": 6, "9y": 6, "A": [2, 3, 5, 6, 7, 10, 11, 12, 13, 15, 16, 19, 20, 21, 23, 24, 25, 26, 28, 29, 30], "AND": 2, "And": [0, 3, 4, 5, 6, 9, 13, 20, 22, 24, 29], "As": [0, 1, 2, 3, 4, 5, 6, 8, 10, 12, 13, 15, 16, 21, 22, 24, 27, 28, 29, 30], "At": [0, 4, 6, 13, 27, 30], "BE": [0, 27], "Be": [2, 18, 20, 27], "Being": 13, "But": [0, 1, 2, 3, 5, 6, 9, 10, 16, 24, 28], "By": [0, 3, 5, 6, 12, 13, 17, 21, 27, 28, 29, 30], "For": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30], "IF": [6, 28, 30], "IN": 26, "If": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 18, 20, 21, 22, 24, 27, 28, 29, 30], "In": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30], "Ising": [5, 12, 28, 29], "It": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 20, 21, 22, 24, 27, 28, 29, 30], "Its": [1, 2, 4, 11], "No": [6, 9, 27, 28, 30], "Not": [0, 1, 5, 6, 28, 29, 30], "OR": 24, "Of": 24, "On": [0, 3, 22, 24, 25, 26, 27], "One": [0, 1, 3, 4, 5, 6, 7, 8, 11, 12, 13, 17, 24, 28, 29, 30], "Or": [0, 1, 6, 27], "Such": [0, 6, 12, 16, 24, 30], "That": [0, 5, 7, 10, 11, 12, 14, 22, 24, 27], "The": [4, 10, 13, 14, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26], "Then": [0, 1, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 21, 27, 29, 30], "There": [0, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 21, 22, 24, 25, 27, 28, 29, 30], "These": [0, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 17, 18, 21, 22, 24, 25, 27, 28, 29, 30], "To": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 21, 24, 28, 29, 30], "With": [0, 5, 6, 8, 9, 10, 11, 12, 14, 16, 19, 21, 22, 24, 27, 28], "_": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 22, 27, 28, 29, 30], "_0": [5, 8, 10, 11, 13, 28, 29], "_1": [2, 5, 6, 8, 10, 11, 12, 13, 14, 21, 28, 29, 30], "_2": [2, 5, 8, 11, 12, 13, 21, 28, 30], "_3": 21, "_4": 21, "_9": [13, 30], "__class__": 10, "__doc__": 6, "__future__": [8, 9], "__init__": 1, "__main__": 2, "__name__": [2, 10], "_auto1": [2, 3, 4, 5, 6, 7, 12, 13, 21, 24, 28, 29], "_auto10": [6, 12], "_auto11": 6, "_auto12": 6, "_auto2": [2, 3, 4, 5, 6, 12, 13, 21, 24], "_auto3": [3, 4, 5, 6, 12, 13, 21], "_auto4": [4, 6, 12, 13, 21], "_auto5": [4, 6, 12, 13, 21], "_auto6": [4, 6, 12, 21], "_auto7": [4, 6, 12, 21], "_auto8": [6, 12], "_auto9": [6, 12], "_build": [0, 20, 22, 26, 27], "_c": 1, "_center": [], "_compon": 11, "_depth": 9, "_export": [15, 16], "_fraction": 9, "_i": [0, 1, 2, 5, 6, 7, 8, 11, 12, 13, 19, 22, 27, 28, 29, 30], "_j": [0, 1, 2, 3, 5, 6, 8, 13, 19, 22, 28, 29, 30], "_k": [13, 29, 30], "_l": 12, "_lambda": 6, "_leaf": 9, "_m": 10, "_multilayer_perceptron": [], "_n": [2, 5, 8, 11, 13, 28, 29, 30], "_node": 9, "_norm": [], "_p": [5, 8, 28, 29], "_ratio": 11, "_sampl": 9, "_split": [6, 9, 22], "_t": [13, 30], "_test": [6, 22], "_varianc": 11, "_weight": 9, "a0": 3, "a0faa0": [9, 10], "a1": [0, 27], "a2": [0, 27], "a3": [0, 27], "a4": [0, 27], "a_": [0, 1, 16, 21, 27, 28], "a_0": [0, 27], "a_1a": [0, 27], "a_2a": [0, 27], "a_3": [0, 27], "a_3a": [0, 27], "a_4": [0, 27], "a_4a": [0, 27], "a_h": 1, "a_i": [0, 1, 2, 12, 27], "a_j": [1, 12], "a_k": [0, 1, 12], "aaron": 26, "ab": [0, 2, 5, 13, 14, 27, 28, 30], "ab_channel": 20, "abandon": 1, "abid": 24, "abil": [0, 10], "abl": [0, 1, 4, 5, 6, 7, 10, 12, 13, 16, 18, 19, 22, 28, 29, 30], "about": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 25, 30], "abov": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 24, 26, 27, 28, 30], "abovement": [6, 22, 27], "abscissa": [13, 29], "absent": 30, "absolut": [0, 2, 5, 6, 13, 27, 28, 29], "absorb": [28, 29], "abstract": 1, "acceler": [13, 30], "accept": [0, 3, 6, 9, 22, 28], "access": [3, 11, 24, 27], "accid": [4, 6], "accompani": [0, 27, 28], "accomplish": [8, 9, 13, 30], "accord": [0, 1, 2, 5, 6, 9, 12, 13, 14, 24, 27, 29, 30], "accordingli": 11, "account": [0, 3, 5, 13, 15, 16, 24, 27], "accumul": [12, 13, 24, 30], "accur": [0, 3, 4, 6, 10, 13, 30], "accuraci": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 27, 28, 29], "accuracy_scor": [0, 1, 10, 27], "accuracy_score_numpi": 1, "achiev": [0, 1, 5, 6, 8, 12, 21, 27, 30], "aco": 24, "acquaint": 20, "acquir": [1, 20, 27], "acr": [], "across": [1, 3, 6, 9, 17, 20, 27], "act": [1, 3, 21], "action": 24, "activ": [0, 2, 3, 4, 9, 15, 23, 25, 27, 30], "actual": [0, 1, 4, 5, 6, 8, 11, 15, 16, 18, 21, 24, 27, 28, 29, 30], "ad": [1, 3, 4, 5, 8, 13, 15, 16, 21, 29, 30], "ada_clf": 10, "adaboostclassifi": 10, "adadelta": [13, 30], "adagrad": 22, "adam": [1, 3, 4, 22, 27], "adapt": [4, 6, 13, 17, 26, 29], "add": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 15, 16, 17, 18, 24, 25, 27, 28, 29, 30], "add_subplot": [1, 7, 12, 14], "addendum": 5, "addit": [0, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 15, 20, 21, 22, 24, 25, 26, 27, 28], "addition": [12, 13, 29, 30], "address": [1, 9, 11, 13, 27, 30], "adjac": [3, 12], "adjoint": [5, 28], "adjust": [0, 5, 12, 13, 29, 30], "admir": [0, 27], "advanc": [4, 6, 12, 26, 27, 30], "advantag": [1, 3, 5, 6, 10, 13, 21, 29, 30], "adversari": 27, "afecionado": 27, "affect": [3, 15], "affin": [0, 3, 8, 11, 28], "afford": 3, "aficionado": 27, "aforement": 14, "african": [], "after": [0, 1, 2, 4, 5, 6, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "afterward": [0, 27], "ag": [0, 7, 27, 28], "ag_0": 2, "again": [0, 1, 4, 5, 6, 7, 8, 10, 11, 12, 13, 22, 24, 27, 28, 29], "against": [1, 4, 7, 10], "agegroup": 7, "agegroupmean": 7, "aggreg": [9, 10], "agorithm": 10, "agre": [5, 6, 24, 28, 29, 30], "agreement": [13, 30], "ahead": 9, "ai": [0, 26], "aid": 11, "aim": [0, 1, 4, 6, 7, 11, 14, 16, 17, 19, 20, 21, 22, 28], "ainv": 5, "airplan": 3, "aka": 5, "al": [0, 2, 4, 16, 17, 26, 27, 28, 29], "alarm": [5, 7], "aldo": 28, "algebra": [0, 3, 5, 13, 20, 28, 29], "algorithm": [0, 1, 2, 4, 5, 6, 7, 8, 13, 14, 16, 20, 21, 22, 24, 26], "align": [0, 2, 5, 6, 7, 8, 13, 24, 27, 28, 29], "all": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30], "allevi": [1, 13, 29], "alloc": [3, 21], "allow": [0, 1, 2, 3, 5, 6, 8, 10, 13, 15, 20, 21, 22, 27, 28, 29, 30], "almost": [0, 1, 6, 8, 11, 13, 24, 29, 30], "alon": [2, 9, 30], "along": [2, 3, 4, 5, 6, 9, 10, 11, 15, 20, 21, 27, 28, 29], "alpha": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 14, 24, 27, 28, 29, 30], "alpha_": [10, 30], "alpha_0": 3, "alpha_1": 3, "alpha_2": 3, "alpha_i": [3, 13], "alpha_k": 13, "alpha_m": 10, "alpha_n": 3, "alpha_opt": 13, "alreadi": [2, 3, 4, 5, 6, 10, 12, 15, 20, 21, 24, 27, 28, 29], "also": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "alter": 1, "altern": [0, 1, 4, 5, 6, 8, 9, 11, 13, 15, 18, 21, 22, 27, 28, 30], "although": [0, 1, 5, 6, 8, 10, 13, 16, 27, 30], "alwai": [0, 3, 5, 6, 12, 13, 16, 22, 24, 27, 28, 29, 30], "am": 4, "ame2016": [0, 27], "american": [], "among": [0, 3, 5, 9, 10, 12, 21, 27, 28], "amongst": 5, "amount": [0, 1, 3, 4, 6, 8, 10, 14, 20], "an": [1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29, 30], "an_": 24, "anaconda": [0, 1, 20, 22, 27], "analogi": 13, "analys": 6, "analysi": [1, 3, 4, 7, 14, 19, 21, 26], "analyt": [2, 3, 5, 6, 7, 12, 13, 17, 20, 22, 27, 28, 29, 30], "analyz": [0, 1, 3, 4, 5, 6, 16, 22, 24, 28, 29], "andrew": 1, "angl": [0, 3, 9, 28, 30], "anharmon": 3, "ani": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 19, 24, 27, 28, 30], "anim": [4, 12], "ann": 12, "annot": [0, 1, 3, 7, 8, 27], "announc": 27, "anonym": 18, "anoth": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 21, 22, 24, 27, 28, 30], "ansatz": [0, 18, 27], "answer": [0, 1, 3, 5, 6, 21, 22, 25, 27], "antialias": [2, 6], "anticip": 4, "anymor": [1, 8], "anyon": [4, 8, 15], "anyth": [1, 15, 16, 24], "anytim": [25, 27], "apach": 1, "apart": [11, 13, 29], "api": [1, 20, 27], "appar": 2, "appear": [0, 1, 3, 13, 21, 24], "append": [1, 3, 4, 8, 9, 13, 19, 27, 30], "appendix": 22, "appli": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 18, 22, 24, 26, 27, 28, 30], "applic": [0, 1, 3, 4, 5, 6, 7, 9, 12, 13, 16, 21, 24, 26, 27, 28, 29, 30], "apply_gradi": 4, "approach": [1, 2, 4, 5, 6, 9, 10, 11, 12, 13, 15, 16, 18, 20, 22, 24, 26, 28, 29], "approch": 22, "appropri": [2, 6, 9, 12, 13, 17, 20, 24], "approv": 27, "approx": [0, 2, 3, 6, 10, 11, 13, 18, 22, 24, 27, 29, 30], "approxim": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11, 13, 19, 22, 24, 27, 28, 29, 30], "apt": [0, 20, 22, 27], "aq": 24, "ar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30], "aragorn": 27, "arang": [1, 3, 4, 6, 7, 9, 10, 12, 13, 27, 30], "arbitrari": [1, 4, 6, 8, 12, 13, 24, 29], "arbitrarili": [0, 1, 11, 27], "arc": 6, "architectur": [3, 4, 12], "archiv": 22, "area": [0, 3, 6, 26, 27], "argmax": [1, 11], "argmin": [4, 10, 14], "argsort": 11, "argu": [1, 13], "argument": [0, 2, 3, 5, 11, 12, 13, 17, 27, 28, 30], "aris": [0, 6, 12, 13, 24, 27, 29], "arithmet": [0, 13, 21, 27], "arm": [6, 28, 30], "armadillo": 21, "around": [0, 1, 4, 5, 6, 11, 18, 22, 24, 27], "arrai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 13, 14, 16, 18, 20, 22, 24, 28, 29, 30], "arrang": [3, 27], "arraybox": 13, "arriv": [0, 6, 9, 11, 21, 24, 27], "arrow": 12, "arrowprop": 8, "art": [0, 1, 20], "articl": [0, 3, 4, 6, 10, 19, 27, 28, 29, 30], "artifici": [0, 2, 7, 12, 26, 27], "artificialneuron": 12, "arug": 13, "arxiv": [3, 4, 30], "asarrai": [0, 6, 9, 28, 30], "asid": 28, "ask": [5, 6, 11, 12, 15, 22], "aspect": [0, 6, 20, 27, 28], "assembl": 3, "assembli": [0, 27], "assert": 4, "assess": [0, 6, 22, 27, 28], "assici": 4, "assign": [0, 7, 8, 9, 12, 13, 14, 15, 23, 25, 26, 27], "associ": [0, 6, 9, 12, 14, 24, 27], "assum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 21, 22, 24, 27, 28, 29, 30], "assumpt": [0, 3, 5, 6, 9, 11, 24, 27, 28], "ast": [0, 5, 6, 27], "astyp": [4, 9, 10], "asymmetri": [0, 27], "asymptot": [4, 6], "atom": [0, 27], "attempt": [0, 4, 6, 7, 8, 10, 27, 28, 30], "attend": 27, "attent": [0, 21, 27], "attract": [0, 10, 27], "attribut": [0, 9, 27], "audi": [0, 27], "audio": [3, 4], "august": [27, 28], "aurelien": [0, 26, 27], "austfjel": 6, "auth": 15, "authent": 15, "author": [0, 1, 10, 24], "authour": 27, "auto": [9, 10, 24], "auto_exampl": [22, 28], "autocor": 24, "autocorrelation_tim": 24, "autocorrelform": 24, "autocovari": 24, "autoencod": [4, 20, 27], "autoencond": 20, "autograd": [20, 27], "autom": [0, 20, 26, 27], "automac": 21, "automag": 27, "automat": [0, 1, 2, 3, 4, 11, 16, 20, 21, 27], "automobil": 3, "autonom": 4, "avail": [0, 1, 4, 6, 10, 11, 20, 21, 22, 23, 25, 26, 27], "averag": [0, 1, 3, 6, 9, 10, 13, 14, 24, 25, 27, 28], "avoid": [0, 4, 5, 6, 9, 11, 13, 18, 21, 28, 30], "awai": [2, 3, 6, 28, 30], "awar": [2, 10], "award": [25, 27], "ax": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 27], "axes3d": [2, 6, 13, 29, 30], "axes_grid1": 6, "axhlin": 8, "axi": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 21, 24, 27, 28, 29, 30], "axiom": 5, "axvlin": [4, 8], "axvspan": 4, "b": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 24, 25, 27, 28, 29, 30], "b1": 8, "b2": 8, "b3": 8, "b_": [0, 1, 21], "b_0": 0, "b_1": [0, 2, 12, 13, 30], "b_2": [0, 13], "b_5": [13, 30], "b_group": 9, "b_i": [0, 1, 2, 12, 27], "b_ia_": [0, 27], "b_ia_i": 0, "b_index": 9, "b_j": [1, 12], "b_k": [0, 1, 12, 13, 30], "b_m": 12, "b_score": 9, "b_valu": 9, "ba": 30, "babcock": 27, "bachelor": [23, 25], "back": [0, 3, 4, 5, 6, 8, 9, 10, 15, 16, 21, 24, 27, 30], "backbon": 21, "backend": [1, 4], "background": [26, 27], "backpropag": 1, "backtrack": 9, "backup": 21, "backward": [1, 2, 4, 12, 21], "bad": [6, 17, 28], "badli": 24, "bag": [9, 20, 27], "bag_clf": 10, "baggin": 27, "baggingboot": 10, "baggingclassifi": 10, "baggingtre": 10, "balanc": [6, 30], "ballpark": 18, "band": 21, "bandwidth": 21, "bar": [0, 6, 11, 22, 27], "barber": 26, "bare": [4, 10], "base": [0, 1, 3, 4, 5, 7, 8, 9, 10, 14, 15, 16, 17, 20, 24, 25, 26, 27, 28, 29], "basi": [5, 7, 8, 10, 11, 12, 13, 21, 28, 29], "basic": [6, 8, 12, 13, 14, 15, 20, 22, 24, 27], "batch": [3, 4, 11, 12, 13, 29], "batch_shap": 4, "batch_siz": [1, 3, 4], "batchnorm": 4, "bay": 7, "bayesian": [5, 20, 26, 27], "becaus": [0, 1, 2, 3, 4, 5, 6, 8, 9, 12, 13, 14, 27, 28, 29, 30], "becom": [0, 1, 2, 5, 6, 7, 9, 12, 13, 24, 27, 28, 29, 30], "been": [0, 1, 2, 3, 4, 5, 6, 11, 12, 13, 20, 21, 22, 27, 28, 30], "befor": [0, 1, 2, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 27, 28, 30], "beforehand": [0, 24, 27], "begin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 21, 24, 25, 27, 28, 29, 30], "behav": [1, 6, 13, 29], "behavior": [0, 1, 13, 27, 29, 30], "behaviour": [12, 30], "behind": [0, 1, 6, 8, 13, 27, 29], "being": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11, 12, 13, 17, 24, 27, 28, 29, 30], "believ": [9, 21], "belong": [7, 8, 9, 13, 14, 29], "below": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 18, 21, 22, 24, 27, 28, 29, 30], "benchmark": 10, "benefici": [1, 13], "benefit": [0, 1, 4, 11, 13, 20, 27, 29, 30], "bengio": [1, 26, 27, 28, 30], "benign": [1, 7], "besid": [4, 5, 29], "bessel": [5, 28], "best": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 18, 25, 27, 28, 29, 30], "beta": [1, 3, 10, 11, 13, 16, 17, 19, 27, 28, 29], "beta1": [], "beta2": [], "beta_": [3, 13, 17, 28], "beta_0": [1, 3, 13, 28], "beta_1": [1, 3, 10, 13, 28, 30], "beta_1m_": 30, "beta_1x_i": 13, "beta_2": [3, 13, 30], "beta_2v_": 30, "beta_3": 3, "beta_i": [3, 30], "beta_j": [13, 28], "beta_k": 13, "beta_linreg": 13, "beta_m": 10, "beta_mg_m": 10, "beta_n": 3, "better": [0, 1, 2, 3, 4, 6, 9, 10, 11, 12, 13, 27, 28, 30], "between": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 24, 27, 28, 29, 30], "beyond": [0, 1, 5, 6, 8, 13, 27, 28, 29, 30], "bf": [13, 14, 19, 21, 24, 29], "bg": 27, "bgd": [13, 30], "bia": [0, 1, 2, 3, 5, 8, 9, 10, 12, 13, 27, 28, 29], "bias": [1, 2, 3, 5, 6, 9, 12, 19, 30], "bibliographi": 22, "big": [0, 1, 2, 5, 6, 14, 19], "bigger": [1, 6, 28], "bigr": 12, "bike": 9, "bilbo": 27, "billion": [3, 12, 20], "bin": [7, 24], "binari": [0, 3, 5, 7, 9, 10, 12, 27], "binarycrossentropi": 4, "bind": 0, "binomi": [20, 24, 27], "binsboot": 6, "bioinformat": 0, "biolog": [1, 12], "bios1100": [20, 27], "bird": [0, 3], "birth": 27, "bishop": [26, 27], "bit": [1, 4, 21, 24, 27], "bitwis": 24, "bivari": 2, "bk": [13, 30], "bla": [21, 27], "black": [8, 9, 14], "block": [6, 10, 20, 21, 24, 27], "blog": 27, "blogpost": 4, "blue": [0, 3], "bm": [], "bmatrix": [0, 1, 3, 5, 7, 8, 11, 13, 21, 27, 28, 29, 30], "bmi": 1, "bodi": [0, 1, 4, 12], "bold": 1, "boldfac": [0, 5, 16, 28, 29], "boldsymbol": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 22, 27, 29, 30], "boltzmann": [12, 20, 27], "book": [17, 22, 26, 27, 28], "book1": 26, "boolean": [4, 17], "boost": [1, 9, 20, 27], "boostrap": 10, "bootstrap": [1, 13, 19, 20, 22, 27, 30], "borrow": 27, "boston_dataset": [], "bot": 8, "both": [0, 1, 4, 5, 6, 8, 9, 10, 13, 14, 15, 16, 17, 20, 21, 22, 24, 25, 27, 28, 29, 30], "bottl": 7, "bound": [8, 12, 30], "boundari": [2, 4, 8, 11, 12], "box": [4, 9], "boyd": [8, 13, 29], "bracket": [4, 24], "brain": [1, 7, 12], "branch": [9, 27], "break": [0, 4, 6, 11, 14, 27, 30], "breast": [5, 7, 11], "breviti": 13, "brew": [0, 20, 22, 27], "brg": 8, "brief": [22, 28], "briefli": [0, 16, 27], "bring": [0, 5, 6, 10, 28, 30], "britt": [25, 27], "broad": 0, "broadli": 27, "brought": [13, 20, 27], "brownle": 4, "browser": [15, 27], "brute": [3, 5, 11, 28], "buffer_s": 4, "bui": 4, "build": [0, 4, 5, 6, 10, 16, 21, 24, 27], "built": [1, 3, 4, 6], "bunch": 11, "busi": [], "byte": [21, 27], "c": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 23, 24, 25, 26, 28, 29, 30], "c1": [8, 11], "c2": [8, 11], "c_": [8, 9, 10, 13, 24, 29, 30], "c_0": 24, "c_1": 12, "c_2": 12, "c_3": 12, "c_4": 12, "c_i": [12, 13, 30], "c_k": 24, "ca": [1, 27], "cach": 10, "cal": [0, 8, 10, 12, 13, 29, 30], "calcul": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 19, 21, 24, 27, 30], "california": 22, "call": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "calor": [0, 28], "cambridg": [13, 26, 29], "can": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29], "cancel": [0, 13, 27, 28], "cancer": [5, 10], "cancerpd": 7, "candid": [8, 9, 10, 30], "cannot": [0, 1, 4, 5, 6, 7, 8, 9, 22, 24, 28, 29], "canopi": [0, 20, 22, 27], "canva": [15, 16, 22, 27], "cap": 5, "capabl": [0, 1, 8, 13, 20, 27], "capac": [2, 25], "capita": [], "caption": 22, "captur": [4, 11, 12, 27], "car": [3, 4], "card": [0, 7, 27], "cardin": 1, "care": [11, 15], "carefulli": [13, 30], "carlo": [0, 6, 20, 24, 26, 27], "carri": [2, 6, 7, 22], "cart": 10, "case": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 14, 15, 16, 20, 21, 22, 27, 30], "casella": 26, "cast": 1, "cat": [3, 4], "catch": 0, "categor": [0, 1, 3, 9, 11, 27], "categori": [0, 1, 3, 7, 10, 12, 14, 27], "categorical_crossentropi": [1, 3], "caus": [0, 5, 6, 24, 27, 28, 29, 30], "causal": 0, "causat": [0, 27], "cax": 1, "cb": [6, 27], "cbar": 1, "cc": [0, 1, 5, 13, 27, 28, 29], "ccc": [5, 12, 29], "cdf": 24, "cdot": [0, 2, 6, 12, 13, 14, 21, 24, 27, 29, 30], "celebr": [13, 29], "cell": 4, "center": [0, 1, 6, 7, 8, 9, 11, 14, 18, 22, 24, 27, 28, 30], "central": [0, 3, 5, 6, 8, 16, 21, 27, 28], "centroid": [14, 24], "centroid_differ": 14, "centuri": 3, "certain": [0, 3, 6, 7, 9, 24, 27, 28], "cg": 13, "cha": [], "chain": [0, 1, 13, 20, 24, 27], "challeng": 15, "chanc": [1, 5, 13, 24, 30], "chang": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 19, 21, 22, 24, 27, 28, 29, 30], "channel": 3, "chapter": [0, 6, 10, 11, 16, 17, 19, 21, 22, 26, 27, 28, 29, 30], "chapter3": [0, 22], "charact": [0, 3, 5, 27, 28, 29], "character": [8, 9, 10, 12, 24], "characterist": [0, 1, 3, 10, 13, 27], "charg": [0, 27], "charl": [], "chase": 4, "chatgpt": [15, 22], "chd": 7, "chddata": 7, "cheap": [5, 28, 29], "cheaper": [1, 13, 30], "check": [1, 3, 4, 5, 11, 13, 15, 16, 19, 21, 27, 30], "checkmark": 3, "checkpoint": 4, "checkpoint_dir": 4, "checkpoint_prefix": 4, "chen": 10, "cheng": 28, "chiaramont": 2, "childcar": 16, "children": 16, "choic": [0, 1, 2, 3, 4, 6, 9, 12, 13, 14, 21, 27, 28, 29, 30], "choleski": [5, 21, 28, 29], "choos": [2, 3, 6, 9, 10, 11, 13, 14, 15, 18, 19, 22, 29], "chosen": [0, 1, 2, 6, 8, 9, 10, 13, 16, 24, 27, 29, 30], "chosen_datapoint": 1, "christian": 26, "christoph": [26, 27], "cifar": 3, "cifar10": 3, "circ": [1, 12, 30], "circl": [0, 8, 12, 28, 30], "circuit": 3, "circumfer": 9, "circumv": [1, 5, 13, 28, 29, 30], "cite": 22, "ckpt": 4, "clariti": 24, "class": [0, 1, 3, 4, 6, 7, 8, 9, 11, 12, 13, 24, 27], "class_nam": [3, 9], "class_val": 9, "class_valu": 9, "classic": [7, 9, 13], "classif": [0, 3, 5, 6, 7, 8, 11, 12, 20, 22, 26, 27, 28], "classifi": [0, 1, 4, 7, 9, 10, 11, 27], "classificaton": 1, "classifii": 10, "clean": 1, "clear": [1, 5, 10, 12, 13, 30], "clearli": [0, 3, 5, 6, 7, 8, 24, 28, 29], "clever": [1, 10], "clf": [0, 6, 8, 9, 10, 27, 28], "clf3": 0, "clf_lasso": 6, "clf_ridg": 6, "cli": 15, "clip": [3, 24], "clone": [15, 25], "close": [0, 1, 2, 4, 6, 8, 9, 11, 12, 13, 14, 18, 24, 26, 27, 29, 30], "closer": [3, 5, 13, 28, 29], "closest": [8, 11, 13, 14], "closur": [20, 27], "cloud": [20, 27], "cluster": [0, 1, 4, 6, 11, 20, 27], "cluster_label": 14, "cm": [1, 2, 3, 6, 8, 13, 29, 30], "cmap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 27], "cmap_arg": 6, "cmd": [9, 15], "cn_": 24, "cnn": 12, "cnn_kera": 3, "cntk": [20, 27], "co": [0, 2, 3, 6, 9, 13, 27], "code": [0, 3, 4, 6, 7, 8, 18, 20, 21, 24, 26], "coef": [0, 27], "coef0": 8, "coef_": [0, 5, 6, 8, 9, 13, 16, 27, 28, 29, 30], "coeff": 5, "coeffici": [0, 3, 5, 6, 7, 8, 9, 13, 18, 21, 27, 28, 30], "coerc": [0, 6, 27], "coin": [10, 24], "coin_toss": 10, "col": [0, 11, 27, 28], "colab": [20, 27], "cold": 9, "colinear": [], "collabor": 22, "collaps": 8, "collect": [2, 6, 10, 11, 17, 20, 24, 26, 27], "collinear": [5, 28, 29], "color": [0, 3, 4, 6, 8, 9, 10, 24, 30], "color_channel": 3, "color_cod": 6, "colorbar": [1, 6], "colsample_bytre": 10, "colsaobject": 10, "column": [0, 1, 2, 5, 6, 7, 8, 9, 11, 12, 16, 17, 18, 21, 27, 28, 29, 30], "columntransform": 9, "com": [4, 6, 15, 16, 20, 22, 26, 27, 29, 30], "combin": [1, 2, 5, 6, 7, 10, 15, 18, 24], "come": [0, 1, 3, 4, 5, 12, 13, 14, 15, 27, 28, 29, 30], "command": [0, 1, 15], "comment": [0, 4, 5, 6, 22], "commerci": [0, 20, 22, 27], "commit": 15, "commod": [0, 27], "common": [0, 1, 3, 5, 6, 7, 9, 11, 13, 14, 16, 22, 24, 27, 28, 29, 30], "commonli": [0, 1, 4, 6, 7, 9, 13, 14, 28, 30], "commun": [0, 12, 15, 22], "commut": 3, "commutatitav": 3, "compact": [0, 1, 3, 5, 6, 7, 9, 11, 12, 13, 14, 27, 28], "compair": 0, "compar": [0, 3, 4, 5, 6, 11, 13, 18, 21, 22, 27, 28, 29, 30], "comparison": [2, 4, 13], "compat": 7, "compens": 30, "compet": 0, "competit": 10, "compil": [0, 1, 3, 4, 13, 20, 21, 27], "complet": [0, 2, 3, 4, 9, 12, 15, 16, 17, 18, 19, 27], "completenn": 12, "complex": [1, 5, 8, 9, 11, 12, 13, 16, 19, 27, 29], "complic": [0, 1, 9, 13, 22, 27, 29, 30], "compoment": 28, "compon": [0, 1, 3, 4, 5, 6, 7, 9, 14, 16, 20, 27, 28, 29], "components_": 11, "compos": [9, 12, 13, 14, 20, 27], "compphys": [0, 6, 16, 20, 22, 23, 25, 26, 27, 28, 29], "compress": [0, 27, 28], "compris": 6, "compromis": [5, 28, 29], "compulsori": [20, 27], "comput": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 18, 20, 21, 22, 23, 24, 26, 27, 28, 29], "computation": [0, 3, 6, 9, 13, 24, 27, 29, 30], "computationalscienceuio": 27, "computerlab": 22, "concaten": [2, 4, 6, 14], "concav": [1, 13, 28, 29], "concentr": 10, "concept": [0, 2, 20, 27, 28], "conceptu": [12, 13, 29], "concern": [0, 1, 4, 7, 27, 29], "concic": 27, "conclud": [0, 5, 13], "conclus": 1, "cond": 2, "conda": [0, 1, 20, 22, 27], "condis": 28, "condit": [0, 2, 4, 5, 6, 8, 9, 11, 13, 24, 27, 28, 30], "conduct": 20, "condwav": 2, "confid": [0, 5, 6, 7, 8, 19, 27, 28], "configur": 3, "confirm": [5, 12], "confus": [5, 6, 7, 10, 21, 28], "confusion_matrix": 9, "congruenti": 24, "conjug": [4, 8], "conjugaci": 13, "conjunct": 3, "connect": [0, 1, 3, 4, 9, 11, 12, 13, 21, 27, 28, 29], "consequ": [5, 6, 8, 10, 12, 13, 28, 29, 30], "conserv": [5, 14, 28, 29], "consid": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 16, 21, 22, 24, 27, 28, 29, 30], "consider": [0, 1, 5, 13, 27, 28, 29], "consist": [1, 2, 3, 4, 6, 12, 13, 22, 24, 28, 29], "constant": [0, 2, 4, 5, 6, 8, 12, 13, 16, 18, 24, 27, 28, 29, 30], "constitu": [0, 27], "constitut": [2, 6], "constrain": [1, 3, 5, 7, 11, 29], "constraint": [5, 6, 8, 13, 28, 29, 30], "construct": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 21, 24, 27, 28], "contact": [0, 27], "contain": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 18, 19, 21, 22, 24, 26, 27, 28, 29, 30], "contemporari": 27, "content": [1, 15, 20, 21, 27, 29, 30], "context": [6, 10, 13, 22, 29, 30], "contigu": 21, "contin": 19, "continu": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 19, 21, 22, 24, 27, 28, 29, 30], "contour": [9, 10, 13], "contourf": [8, 9, 10], "contrast": [1, 4, 9, 10, 12, 27, 30], "contribut": [0, 3, 5, 13, 18, 24, 27, 28, 29, 30], "contributor": [0, 22], "control": [0, 1, 3, 9, 13, 15, 20, 27], "conv": [3, 4], "conv2d": [3, 4], "conv2dtranspos": 4, "convei": 27, "conveni": [5, 6, 12, 13, 21, 22, 27, 29, 30], "convent": [12, 28], "converg": [1, 2, 4, 5, 8, 13, 14, 18, 28, 29], "convergencewarn": [], "convers": 30, "convert": [0, 1, 4, 5, 9, 11, 13, 21, 27, 28, 29], "converttomatrix": 4, "convex": [4, 5, 7, 28, 30], "convinc": [13, 29], "convolut": [1, 4, 20, 27], "cool": [4, 9], "coolwarm": 6, "coordin": [5, 12, 14, 28, 29, 30], "coorel": [], "copi": [0, 1, 14, 15, 28], "core": 10, "corel": 27, "coronari": 7, "corr": [5, 7, 11, 28], "correalt": [11, 20], "correct": [0, 1, 2, 3, 4, 5, 7, 13, 15, 21, 24, 27, 28, 29], "correctli": [1, 2, 6, 7, 10, 18, 19, 22], "correl": [0, 1, 3, 5, 6, 7, 10, 12, 13, 20, 24, 27, 29, 30], "correlation_matrix": [5, 7, 11, 28], "correspond": [0, 3, 5, 6, 8, 9, 11, 12, 20, 21, 22, 24, 27, 28, 29], "cortex": 12, "cosin": [3, 6], "cost": [0, 2, 3, 5, 6, 7, 8, 9, 12, 13, 16, 17, 18, 19, 22, 27], "cost_deep_grad": 2, "cost_funct": 2, "cost_function_deep": 2, "cost_function_deep_grad": 2, "cost_function_grad": 2, "cost_grad": 2, "cost_histori": [], "cost_ol": [], "cost_ridg": [], "cost_sum": 2, "costol": [13, 30], "could": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 21, 22, 24, 27, 28, 29, 30], "coulomb": [0, 27], "count": [0, 9, 15, 23, 24, 25, 27], "counteract": 30, "counterpart": 27, "countor": 13, "coupl": [4, 5, 6], "cours": [0, 1, 3, 5, 11, 15, 16, 17, 22, 25, 28], "coursework": 15, "courvil": [26, 27, 28, 30], "cov": [5, 6, 11, 21, 24, 27, 28], "cov_xi": [5, 11, 28], "cov_xx": [5, 11, 28], "cov_yi": [5, 11, 28], "covari": [0, 7, 20, 21, 27, 29], "covariance_matrix": [5, 11, 14], "cover": [0, 5, 20, 25, 26, 28, 29], "covert": [0, 27], "covxi": 24, "covxx": 24, "covxz": 24, "covyi": 24, "covyz": 24, "covzz": 24, "cpu": 1, "craft": 3, "creat": [1, 3, 4, 5, 9, 10, 11, 12, 15, 18, 19, 20, 27, 30], "create_biases_and_weight": 1, "create_convolutional_neural_network_kera": 3, "create_neural_network_kera": 1, "create_x": [5, 11], "credit": [0, 7, 25, 27], "crim": [], "crime": [], "criteria": [0, 4, 9, 10, 14, 24, 27], "criterion": [9, 10, 13, 18, 29, 30], "critic": [6, 22, 28], "critiqu": 22, "cross": [0, 1, 3, 7, 9, 10, 13, 15, 20, 24, 27, 28, 29, 30], "cross_entropi": 4, "cross_val_scor": 6, "cross_valid": [7, 10], "crossvalid": 6, "crucial": [1, 24, 30], "cs231": 3, "csr_matrix": [21, 27], "csv": [0, 4, 6, 7, 9], "ctnk": 1, "cubic": 0, "cumbersom": 5, "cumsum": [10, 11, 27], "cumul": [7, 10, 24, 30], "cumulative_heads_ratio": 10, "cup": 5, "current": [1, 2, 3, 4, 13, 14, 15, 16, 26, 29, 30], "curs": [0, 28], "curv": [6, 7, 10, 12, 22], "curvatur": [13, 29, 30], "custom": [6, 14], "custom_cmap": [9, 10], "custom_cmap2": [9, 10], "cutpoint": 9, "cv": [6, 7, 10], "cvxbook": [13, 29], "cvxopt": [5, 8, 28], "cycl": [1, 12], "d": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 21, 24, 25, 27, 28, 29, 30], "d2_g_t": 2, "d_f": [13, 29], "d_g_t": 2, "d_net_out": 2, "da": 3, "dagger": [5, 21, 28, 29], "dai": [1, 9, 20], "damp": 3, "darget": 9, "darkr": 24, "dat": [0, 27], "dat_id": [0, 6, 7, 9, 27], "data": [2, 4, 5, 8, 10, 12, 13, 14, 16, 19, 21, 22, 26, 29, 30], "data1": 14, "data2": 14, "data3": 14, "data4": 14, "data_id": [0, 6, 7, 9, 27], "data_indic": 1, "data_panda": 27, "data_path": [0, 6, 7, 9, 27], "databas": 1, "datafil": [0, 6, 7, 9, 27], "datafram": [0, 4, 5, 7, 9, 11, 27, 28], "datapoint": [1, 5, 6, 7, 11, 13, 16, 29, 30], "datasci": [15, 16], "dataset": [0, 4, 6, 7, 8, 9, 10, 11, 13, 14, 16, 22, 27, 29, 30], "datatyp": 4, "date": [15, 18, 22, 27, 28, 29, 30], "daughter": 10, "david": 26, "dbh": 1, "dbo": 1, "dcomposit": 21, "ddot": 2, "dead": 1, "deadlin": 15, "deal": [0, 1, 3, 5, 6, 8, 11, 13, 14, 19, 21, 24, 27, 28, 29, 30], "dealt": 0, "debt": 7, "debug": [0, 5, 6, 28, 29, 30], "decad": [0, 3, 30], "decai": [0, 13, 24, 27], "decemb": [25, 27], "decent": 10, "decid": [0, 2, 3, 5, 6, 9, 18, 28, 29, 30], "decim": [0, 27], "decis": [0, 1, 8, 11, 20, 26, 27], "decision_funct": 8, "decision_tre": 9, "decisiontreeclassifi": [9, 10], "decisiontreeregressor": [0, 9, 10], "declar": [0, 4, 21, 27], "decompos": [5, 6, 21, 28, 29], "decomposit": [0, 6, 12, 27], "decompost": [5, 28, 29], "deconvolut": 3, "decorrel": [10, 13, 30], "decreas": [1, 2, 4, 5, 6, 10, 11, 13, 19, 29, 30], "deduc": [0, 27], "deep": [3, 7, 12, 13, 20, 26, 28, 29, 30], "deep_neural_network": 2, "deep_param": 2, "deep_tree_clf": [9, 10], "deep_tree_clf1": 9, "deep_tree_clf2": 9, "deepen": [5, 20, 27], "deeper": [0, 3, 4, 27], "deeplearningbook": [26, 27, 29, 30], "deer": 3, "def": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 24, 27, 28, 29, 30], "def_covari": 24, "default": [0, 1, 2, 4, 6, 7, 21, 27, 28], "default_tim": 4, "defect": [5, 28, 29], "defici": [5, 28, 29], "defin": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 28, 29, 30], "definit": [1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 21, 24, 28, 29, 30], "defint": 24, "degre": [3, 5, 6, 8, 9, 10, 11, 15, 16, 19, 22, 24, 27, 29, 30], "deisenroth": 28, "del": 1, "delet": [6, 15], "delimit": 4, "deliv": [15, 23, 27], "delta": [0, 2, 3, 6, 8, 12, 13, 14, 27, 30], "delta_": [1, 21], "delta_0": 3, "delta_1": 3, "delta_2": 3, "delta_3": 3, "delta_4": 3, "delta_5": 3, "delta_h": [0, 1, 27], "delta_j": [3, 12], "delta_k": 12, "delta_l": [1, 3], "delta_momentum": [13, 30], "delta_n": [0, 3, 27], "delug": 20, "delv": 0, "demand": [13, 29], "demonstr": [0, 3, 5, 6, 7, 11, 12, 20, 27, 28, 29], "den": 4, "denomin": [1, 5, 30], "denot": [1, 2, 6, 7, 13, 24, 29, 30], "dens": [1, 3, 4], "densiti": [0, 2, 6, 24], "depart": [25, 27, 28, 29, 30], "depend": [0, 1, 2, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 29, 30], "depict": 24, "deploy": [0, 20, 22, 27], "depth": [0, 3, 9, 10, 21], "deriv": [0, 1, 2, 6, 7, 8, 10, 11, 13, 18, 20, 22, 27], "derivati": 13, "derivative_fn": 13, "descend": [5, 9, 11, 28, 29], "descent": [0, 1, 3, 7, 8, 12, 27, 28], "describ": [0, 2, 4, 5, 6, 8, 10, 11, 12, 13, 19, 21, 22, 27, 30], "descript": [0, 8, 9, 22, 27], "design": [0, 1, 3, 4, 5, 6, 7, 10, 11, 12, 13, 17, 18, 22, 27, 29, 30], "designmatrix": [0, 27], "desir": [0, 2, 4, 5, 13, 14, 27, 28, 29, 30], "desktop": 15, "despit": [1, 12], "destroi": 21, "det": [5, 21, 28, 29], "detail": [0, 6, 11, 13, 14, 18, 21, 22, 28, 29, 30], "detect": [3, 8, 12], "determin": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 18, 21, 24, 27, 28, 29, 30], "determinist": [7, 13, 24, 29, 30], "dev": [1, 22], "develop": [0, 3, 5, 8, 10, 11, 12, 20, 21, 22, 27, 28], "deviat": [0, 1, 2, 4, 5, 6, 17, 18, 19, 22, 24, 27, 28, 30], "devis": 12, "df": [4, 8, 11, 13, 27], "df1": 27, "di": [], "diag": [5, 8, 28, 29, 30], "diagnost": [1, 10], "diagon": [0, 5, 7, 13, 18, 19, 21, 24, 27, 28, 29, 30], "diagonaliz": [5, 28, 29], "diagram": 10, "diagsvd": 6, "dice": [6, 24], "dict": [6, 8], "dictionari": [], "did": [0, 1, 5, 6, 7, 10, 11, 14, 16, 22, 27], "die": 1, "diff": 2, "diff1": 2, "diff2": 2, "diff_ag": 2, "diffeent": 8, "differ": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29], "differenti": [0, 3, 16, 20, 21, 27, 28, 29], "difficult": [0, 1, 6, 10, 13, 24, 27, 30], "difficulti": [0, 1, 13, 27, 29], "diffonedim": 2, "digit": [0, 1, 3, 4, 6, 25, 27], "dilemma": [13, 30], "dilut": 1, "dim": [4, 11, 14, 21], "dimens": [0, 1, 2, 3, 4, 5, 8, 11, 14, 16, 21, 27, 28, 29], "dimension": [0, 4, 5, 6, 9, 11, 13, 14, 19, 20, 21, 22, 27, 28, 29, 30], "dimensionless": [0, 3, 27], "diment": 21, "diminish": 30, "dimnsion": 4, "diod": 3, "direct": [0, 1, 2, 4, 11, 12, 13, 14, 27, 28, 29, 30], "directli": [1, 4, 5, 6, 18, 24, 28, 29], "disadvantag": [0, 27, 30], "disappear": [3, 6], "disc_loss": 4, "disc_tap": 4, "discard": [6, 11], "disciplin": [0, 3, 12], "disclaim": 24, "discord": 27, "discourag": [13, 15, 29], "discov": [0, 27], "discover": 5, "discret": [1, 3, 5, 7, 13], "discrimin": [4, 7, 10, 11], "discriminator_loss": 4, "discriminator_loss_list": 4, "discriminator_model": 4, "discriminator_optim": 4, "discuss": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30], "diseas": 7, "disguis": [6, 28, 30], "disord": [1, 7], "displai": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 22, 24, 27, 28], "displaystyl": [0, 5, 17, 27, 28, 29, 30], "disregard": [0, 27], "dissimilar": [11, 14], "dist": 14, "distanc": [8, 9, 11, 14, 24], "distance_list": 9, "distinct": [3, 7, 8, 9, 10, 14], "distinctli": 8, "distinguish": [0, 4, 7, 8, 24, 27], "distplot": [], "distribut": [0, 1, 4, 6, 7, 10, 11, 13, 14, 18, 19, 20, 21, 22, 27, 28, 29, 30], "distrubut": [0, 20, 22, 27], "dive": [0, 8, 21, 27], "diverg": [1, 13, 29, 30], "divid": [0, 1, 3, 5, 6, 7, 8, 9, 11, 12, 18, 24, 27, 28, 30], "divis": [6, 8, 9, 13, 18, 21, 24, 30], "dna": 7, "dnn": [0, 1, 2, 4, 12, 27], "dnn1": 4, "dnn2_gru2": 4, "dnn_kera": 1, "dnn_model": 1, "dnn_numpi": 1, "dnn_scikit": [0, 1, 27], "do": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 27, 28, 29], "doc": [0, 15, 16, 20, 22, 23, 25, 26, 27], "document": [4, 13, 15], "doe": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 17, 18, 21, 22, 24, 27, 30], "doesn": [3, 9, 12, 27], "dog": [1, 3, 4], "domain": [5, 8, 13, 22, 29], "domin": [0, 27], "don": [0, 1, 3, 5, 6, 8, 11, 13, 15, 16, 20, 22, 27, 28, 30], "done": [0, 2, 3, 4, 5, 6, 9, 10, 11, 13, 16, 21, 22, 27, 28, 29, 30], "dot": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 18, 21, 22, 24, 27, 28, 29, 30], "doubl": [3, 4, 16, 21, 27], "doubli": 1, "doubt": 22, "down": [0, 3, 6, 9, 11, 12, 13, 29, 30], "download": [0, 1, 3, 5, 6, 15, 21, 26, 27], "downsampl": 3, "dozen": 1, "dq": 6, "drag": 13, "dramat": 11, "drastic": 4, "draw": [4, 6, 10, 13, 29], "drawback": [0, 1, 3, 13, 28, 29, 30], "drawn": [1, 4, 6, 7, 11, 24, 27], "drive": [3, 4], "driven": 3, "drop": [0, 1, 5, 6, 11, 13, 24, 27, 28, 29], "dropna": [0, 6, 27], "dropout": 4, "dt": [2, 3, 13, 24], "dtype": [0, 1, 3, 4, 14, 21, 27], "dub": [0, 27], "due": [1, 2, 5, 6, 8, 10, 12, 13, 18, 25, 27, 28, 29, 30], "dummi": [], "dure": [0, 1, 3, 4, 8, 9, 11, 20, 22, 27, 30], "dwell": [], "dwh": 1, "dwo": 1, "dx": [2, 3, 8, 24], "dx_1": 24, "dx_1p": 6, "dx_2p": 6, "dx_mp": 6, "dx_n": 24, "dxp": 6, "dy": [1, 8, 24], "dynam": 4, "dz": 8, "e": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 24, 25, 27, 28, 29, 30], "e_": [0, 2, 27], "each": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 23, 24, 25, 27, 28, 29, 30], "eapprox": [0, 27], "earli": [1, 13, 30], "earlier": [0, 5, 7, 8, 9, 11, 12, 13, 27, 28], "earthexplor": 6, "eas": [6, 9, 14], "easi": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 20, 21, 27, 28, 29, 30], "easier": [5, 6, 8, 9, 13, 15, 22, 24, 27, 28, 29], "easiest": [13, 18], "easili": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 27, 28, 29, 30], "eastern": [25, 27], "ebind": [0, 27], "eblock": 9, "econometr": 27, "economi": 5, "ecosystem": [20, 27], "ect": 23, "edg": 3, "edgecolor": 6, "editor": 15, "edu": [13, 22, 29], "educ": [0, 22, 27], "eff": 24, "effect": [1, 4, 10, 13, 16, 17, 18, 24, 30], "effic": 1, "effici": [0, 3, 10, 13, 20, 21, 24, 27, 30], "efron": 6, "egrad": 13, "eig": [5, 11, 13, 21, 24, 27, 28, 29, 30], "eigen": 24, "eigenpair": [5, 11, 28, 29], "eigenvalu": [0, 5, 8, 11, 13, 21, 27, 28, 29, 30], "eigenvector": [5, 11, 13, 28, 29], "eight": [21, 27], "eigval": [21, 24, 27], "eigvalu": [11, 13, 29, 30], "eigvec": [21, 24, 27], "eigvector": [11, 13, 29, 30], "eir": [25, 27], "eispack": [21, 27], "either": [1, 5, 6, 7, 8, 9, 10, 11, 13, 18, 22, 24, 27, 28, 29, 30], "eivind": 25, "eivinsto": 25, "ekstr\u00f8m": 4, "elabor": 24, "elarn": 3, "electr": [0, 3, 12, 27], "electron": 27, "eleg": 11, "element": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 19, 20, 21, 22, 26, 28, 30], "elementari": [10, 13, 21], "elementwis": [3, 13], "elementwise_grad": [2, 13], "elessar": 27, "elif": 14, "elim": 21, "elimin": [3, 8], "elin": [25, 27], "ell_": [], "ellipsi": 16, "els": [1, 3, 4, 7, 9, 12, 13, 16, 21], "elu": 1, "elus": [0, 27], "email": [23, 25, 27], "embed": [0, 11, 28], "embodi": [6, 22], "emit": 24, "emner": 26, "emph": 30, "emphas": [0, 10, 20, 27], "emphasi": [0, 20, 26, 27], "empir": [1, 11, 24], "emploi": [0, 1, 5, 6, 11, 13, 24, 27, 28, 29], "employ": 0, "empti": [6, 10, 15], "emul": 12, "en": [20, 22, 26], "enabl": 11, "enbodi": 6, "encod": [0, 3, 5, 9, 11, 14, 27, 28, 29], "encompass": [0, 22, 24], "encount": [0, 1, 5, 7, 13, 15, 22, 24, 27, 28, 29], "encourag": [15, 22], "end": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 24, 25, 27, 28, 29, 30], "endpoint": [3, 6], "energi": [0, 4, 6], "enforc": 12, "eng": 26, "engin": [0, 1, 3, 4, 20, 27], "english": 22, "enocurag": 22, "enorm": 3, "enough": [0, 6, 13, 27, 29, 30], "ensembl": [1, 9, 27], "ensur": [0, 1, 2, 3, 5, 6, 11, 13, 18, 24, 28, 29, 30], "entail": 27, "enter": [5, 6, 28, 29, 30], "enthought": [0, 20, 22, 27], "entir": [1, 3, 7, 9, 20, 24, 27, 30], "entiti": [9, 12, 21, 27], "entri": [0, 5, 8, 11, 12, 21, 27, 28, 30], "entropi": [1, 3, 7, 10, 13, 27, 29, 30], "enumer": [0, 1, 2, 3, 4, 6, 8, 27, 28, 30], "env": 24, "environ": [2, 20, 22, 27], "environemnt": 15, "eo": [0, 6], "eol": 0, "eosfit": 0, "epoch": [0, 1, 3, 4, 12, 13, 27, 30], "epsilon": [0, 5, 6, 7, 13, 22, 27, 28, 29, 30], "epsilon_": [0, 27], "epsilon_0": [0, 27], "epsilon_1": [0, 27], "epsilon_2": [0, 27], "epsilon_i": [0, 27, 28], "eq": [3, 13, 14, 21, 24, 29], "eqnarrai": [3, 5, 6], "equal": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 16, 18, 21, 22, 24, 27, 28, 29, 30], "equat": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 17, 19, 21, 24, 27, 30], "equilibrium": [2, 12], "equiv": [3, 13, 21, 24, 29, 30], "equival": [0, 1, 5, 7, 8, 11, 13, 20, 21, 27, 28, 29, 30], "erf": 24, "eriador": 27, "err": [0, 10], "err_": 6, "err_sqr": 2, "errat": [13, 29, 30], "erron": 2, "error": [1, 2, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 24, 30], "error_estimate_corr_tim": 24, "error_hidden": 1, "error_output": 1, "escap": [13, 29, 30], "especi": [1, 3, 9, 12, 13, 15, 18, 22, 30], "essenti": [0, 5, 6, 9, 10, 12, 14, 15, 22, 24, 28, 29], "establish": [0, 6, 10, 11, 16, 22], "estim": [0, 1, 5, 6, 7, 10, 11, 13, 19, 20, 24, 27, 28, 29, 30], "estimated_mse_fold": 6, "estimated_mse_kfold": 6, "estimated_mse_sklearn": 6, "et": [0, 2, 4, 16, 17, 26, 27, 28, 29], "eta": [0, 1, 3, 8, 12, 13, 18, 27, 29, 30], "eta0": [8, 13], "eta_": 13, "eta_j": 30, "eta_t": [13, 30], "eta_v": [0, 1, 3, 27], "etc": [0, 1, 3, 5, 7, 8, 9, 11, 12, 13, 14, 20, 21, 22, 24, 28, 29, 30], "ethic": 20, "euclidean": [0, 14, 28, 30], "evalu": [0, 2, 3, 4, 5, 6, 9, 13, 15, 16, 17, 19, 22, 24, 27, 28, 29, 30], "evalut": [13, 22], "even": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 20, 21, 24, 27, 28, 29, 30], "evenli": 4, "event": [5, 7, 10, 24], "eventu": [0, 5, 6, 11, 12, 13, 22, 25, 28, 29, 30], "everi": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 14, 15, 20, 24, 25, 27, 28, 29, 30], "everyth": [4, 12, 16, 18], "everywher": [4, 13, 29], "evolv": 0, "exact": [0, 5, 11, 12, 13, 21, 24, 27, 28], "exactli": [0, 3, 4, 6, 12, 18, 20, 28, 30], "exam": 27, "examin": 6, "exampl": [0, 5, 11, 12, 13, 15, 16, 18, 20, 21, 22, 24, 26], "exce": [1, 12, 13, 30], "excel": [0, 1, 4, 5, 10, 22, 27, 28], "except": [3, 4, 6, 8, 9, 21], "excess": [0, 27], "excit": 0, "exclud": [1, 6, 12, 28, 30], "exclus": [0, 1, 3, 6, 24, 27], "execut": [2, 5, 13, 15, 28, 29], "exemplifi": [13, 30], "exercic": [25, 27], "exercis": [5, 20, 22, 23, 25, 27, 29, 30], "exhaust": 6, "exhibit": [0, 5, 6, 8, 27, 28], "exist": [0, 1, 2, 3, 5, 6, 7, 8, 9, 13, 19, 21, 22, 27, 29], "exit": [5, 21, 28, 29], "exp": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 16, 17, 19, 24, 28, 29, 30], "exp_term": 1, "expand": [5, 7, 11, 13, 29], "expans": [0, 3, 5, 8, 10, 12, 13, 27, 28, 29], "expect": [0, 1, 5, 6, 7, 11, 12, 13, 15, 18, 20, 22, 27, 28, 30], "expectation_value_of_h_wrt_p": 24, "expens": [6, 10, 13, 16, 29, 30], "experi": [0, 1, 6, 8, 13, 15, 20, 22, 27, 28, 29], "experiment": [0, 4, 6, 9, 24, 27], "expert": [1, 9], "explain": [0, 6, 9, 10, 11, 13, 16, 19, 22, 27, 29], "explained_variance_ratio_": 11, "explanatori": [0, 27], "explicit": [0, 3, 6, 13, 21, 22, 27, 28, 29, 30], "explicitli": [0, 4], "explod": 1, "exploit": [0, 3, 12, 13, 27], "explor": [1, 4, 6, 8, 13, 18, 20, 22, 27, 29, 30], "expon": 1, "exponenti": [0, 1, 5, 6, 10, 13, 24, 27, 29], "export": [9, 15, 16], "export_graphviz": 9, "export_text": 9, "exporttext": 9, "expos": 20, "express": [0, 2, 3, 5, 6, 7, 10, 12, 13, 18, 21, 22, 24, 27, 29, 30], "exptmean": 24, "exptvari": 24, "extend": [0, 2, 7, 11, 13, 20, 27, 30], "extens": [0, 12, 15, 20, 27], "extent": [0, 1, 6, 26], "extern": [3, 6, 9], "extra": [1, 3, 5, 15, 25, 27, 28, 29], "extract": [0, 3, 5, 6, 7, 8, 11, 13, 16, 17, 21, 27, 28], "extrapol": [0, 27], "extrem": [0, 1, 4, 5, 6, 7, 8, 9, 13, 15, 16, 21, 28, 29, 30], "extremum": [13, 29], "extrins": 11, "ey": [0, 5, 6, 13, 14, 18, 21, 27, 28, 29, 30], "f": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18, 19, 21, 24, 25, 27, 28, 29, 30], "f1": 13, "f11": [0, 27], "f12": [0, 27], "f13": [0, 27], "f1_grad": 13, "f1d": 13, "f2": 13, "f2_grad_x1": 13, "f2_grad_x1_analyt": 13, "f2_grad_x2": 13, "f2_grad_x2_analyt": 13, "f3": 13, "f3_grad": 13, "f3_grad_analyt": 13, "f4": 13, "f4_grad": 13, "f4_grad_analyt": 13, "f5": 13, "f5_grad": 13, "f6": 13, "f6_for": 13, "f6_for_grad": 13, "f6_grad_analyt": 13, "f6_while": 13, "f6_while_grad": 13, "f7": 13, "f7_grad": 13, "f7_grad_analyt": 13, "f8": 13, "f8_grad": 13, "f9": [0, 13, 27], "f9_altern": 13, "f9_alternative_grad": 13, "f9_grad": 13, "f_": 10, "f_0": [3, 10], "f_1": [10, 13, 29], "f_2": [12, 13, 29], "f_3": 12, "f_d": 24, "f_grad": 13, "f_grad_analyt": 13, "f_i": [0, 6, 12, 16], "f_m": [3, 10], "f_n": 3, "f_vec": 2, "face": [13, 27, 29], "facecolor": [6, 8, 24], "facil": [0, 20], "facilit": 12, "fact": [0, 1, 3, 5, 9, 11, 12, 13, 27, 28, 29], "factor": [0, 1, 3, 5, 6, 9, 10, 11, 13, 21, 24, 27, 28, 29], "factori": 13, "fade": 6, "fafab0": [9, 10], "fail": [0, 6, 13, 25, 27, 29], "failur": 7, "fairli": [1, 2, 18, 24, 30], "faisal": [16, 28], "fake": 4, "fake_loss": 4, "fake_output": 4, "fall": [8, 9, 23], "fals": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 14, 16, 17, 21, 27, 28, 29, 30], "famili": [0, 7, 8, 24, 28, 30], "familiar": [0, 3, 5, 6, 8, 15, 20, 21, 22, 24, 27], "famou": [6, 12], "far": [0, 3, 4, 5, 6, 8, 11, 12, 13, 14, 16, 27, 28, 29], "fashion": [0, 9, 10, 27], "fast": [1, 3, 6, 10, 12, 13, 20, 24, 27, 29, 30], "faster": [1, 11, 13, 30], "fastest": [13, 21, 29], "favor": 7, "favorit": 24, "fc": 3, "featur": [0, 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 15, 17, 18, 19, 20, 24, 27, 29, 30], "feature_nam": [1, 7, 9], "feautur": 9, "fed": 1, "feed": [0, 2, 3, 11, 20, 27], "feed_forward": 1, "feed_forward_out": 1, "feed_forward_train": 1, "feedback": [4, 27], "feeddorward": 4, "feedforward": [1, 4, 12], "feel": [0, 5, 6, 11, 13, 15, 16, 18, 20, 22, 25, 27], "feet": [], "felt": 22, "fetch": [6, 15], "few": [1, 3, 4, 5, 9, 17, 18, 24, 27], "fewer": [0, 9, 11, 27], "ffnn": [1, 12], "field": [0, 3, 6, 12, 20], "fifth": [0, 6, 27], "fig": [0, 1, 2, 3, 4, 6, 7, 12, 13, 14, 22, 27], "fig_id": [0, 6, 7, 9, 27], "figaxi": 24, "figsiz": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 27], "figur": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 20, 22, 27, 28, 29, 30], "figure_id": [0, 6, 7, 9, 27], "figurefil": [0, 6, 7, 9, 27], "file": [0, 4, 5, 6, 7, 9, 15, 22, 27], "file_prefix": 4, "filenam": 27, "fill": [5, 9, 18, 28, 29], "filter": [3, 4], "final": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 22, 23, 24, 25, 27, 29], "financ": 0, "find": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 22, 24, 27, 28, 29, 30], "fine": [0, 14], "finish": 2, "finit": [3, 5, 6, 12, 13, 17, 24, 28, 29], "finnicki": 15, "first": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 21, 22, 24, 25, 26, 28, 30], "first_moment": 30, "first_term": 30, "firsteigvector": 11, "fit": [1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 17, 18, 19, 22, 24, 28, 30], "fit_beta": 28, "fit_intercept": [0, 5, 6, 16, 28, 29, 30], "fit_mod": 9, "fit_theta": [6, 30], "fit_transform": [0, 6, 8, 9, 11, 15, 19], "fiti": [0, 27], "five": [0, 9, 27, 28], "fix": [0, 3, 4, 6, 10, 11, 12, 13, 22, 27], "flag": 4, "flat": [12, 13, 29, 30], "flatten": [1, 3, 4, 5, 21], "flexibl": [1, 6, 8, 10, 12, 27, 30], "flip": [25, 27], "float": [0, 3, 4, 5, 9, 11, 13, 14, 21, 27, 28, 29], "float32": [4, 9], "float64": [4, 21, 27], "flop": [5, 21, 28, 29], "flow": [1, 4, 12], "fluctuat": 5, "fly": 11, "fm": 0, "fmax": 3, "fmesh": 13, "fn": 7, "focu": [0, 3, 4, 5, 6, 15, 20, 22, 26, 27, 28, 29, 30], "focus": [1, 6, 7, 21, 28, 30], "fold": [6, 9, 22], "folder": [0, 4, 6, 15, 22, 27], "follow": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30], "font": [7, 24, 27], "fontdict": 24, "fontsiz": [1, 6, 8, 9, 10, 24], "fontweight": 1, "footprint": 3, "foral": [8, 28], "forc": [0, 5, 6, 10, 11, 28, 29, 30], "forcast": 4, "forecast": [4, 12], "forest": [0, 1, 9, 20, 27], "forget": [11, 30], "form": [0, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 29, 30], "formal": [3, 4, 14, 18, 24], "format": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 20, 24, 26], "format_data": 4, "formatstrformatt": [6, 13, 29, 30], "formul": [4, 6, 11, 14], "formula": [3, 13, 24, 29], "forth": [4, 12], "fortran": [0, 20, 21, 27], "fortran2003": [20, 27], "fortran2008": 22, "fortran90": 24, "fortun": [0, 11, 28], "forward": [0, 3, 6, 20, 21, 27], "found": [1, 2, 4, 5, 6, 12, 13, 19, 22, 27, 28, 30], "foundat": [20, 27], "four": [4, 5, 6, 8, 12, 21, 23, 25, 27, 29], "fourier": [0, 27], "fourierdef1": 3, "fourierdef2": 3, "fourierseriessign": 3, "fourth": [12, 27, 28], "fp": 7, "frac": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "fraction": 9, "frame": 7, "framework": [1, 8, 10, 24], "frank": [5, 11], "frankefunct": [5, 6, 11], "fredli": [25, 27], "free": [0, 6, 11, 13, 15, 16, 18, 20, 21, 22, 24, 25, 26, 27], "freecodecamp": 20, "freedom": [5, 29], "freeli": [0, 22], "freez": 15, "frequenc": [3, 6, 7, 24], "frequent": [0, 8, 9, 13, 29], "frequentist": 20, "fresh": 10, "fridai": [15, 25, 27], "friedman": [6, 19, 22, 26, 27], "friendli": 4, "fro": 22, "frodo": 27, "frog": 3, "from": [0, 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26], "from_cod": 9, "from_logit": [3, 4], "from_tensor_slic": 4, "front": [0, 4, 5, 27, 28, 29], "frustrat": 15, "fulfil": [2, 5, 12, 28, 29], "full": [1, 3, 5, 7, 9, 10, 13, 24, 27, 28, 29, 30], "full_matric": [5, 28, 29], "fulli": [3, 6, 12, 24], "fun": [20, 27], "func": 2, "function": [2, 3, 4, 5, 9, 14, 15, 16, 17, 18, 19, 20, 21], "functionali": 11, "fundament": [0, 6, 20, 27], "funtion": 2, "further": [2, 7, 9, 19, 27], "furthermor": [0, 3, 5, 6, 7, 11, 12, 13, 20, 22, 27, 28, 29, 30], "futur": [0, 4, 8, 9, 27], "fy": [15, 22, 23, 25, 26, 27], "fys4155": 22, "fys5419": [26, 27], "fys5429": [26, 27], "f\u00f8470": [25, 27], "g": [0, 1, 2, 3, 4, 6, 8, 9, 10, 11, 13, 15, 18, 24, 27, 28, 29, 30], "g0": 2, "g_": [2, 9, 10, 30], "g_0": 2, "g_1": [2, 10], "g_2": [2, 10], "g_analyt": 2, "g_dnn_ag": 2, "g_euler": 2, "g_i": 2, "g_m": [3, 10], "g_n": 3, "g_re": 2, "g_t": [2, 30], "g_t_d2t": 2, "g_t_d2x": 2, "g_t_dt": 2, "g_t_hessian": 2, "g_t_hessian_func": 2, "g_t_jacobian": 2, "g_t_jacobian_func": 2, "g_trial": 2, "g_trial_deep": 2, "g_vec": 2, "gain": [1, 5, 7, 9, 10, 13, 28, 29], "galleri": [0, 27], "game": 4, "gamge": 27, "gamma": [0, 2, 8, 9, 10, 11, 13, 27, 29], "gamma1": 8, "gamma2": 8, "gamma_": [0, 27], "gamma_0": 10, "gamma_1": 10, "gamma_1x": 10, "gamma_i": [0, 8, 24, 27], "gamma_j": 13, "gamma_k": [13, 29], "gamma_m": 10, "gamma_x": [0, 27], "gap": 8, "gate": [4, 12], "gather": [0, 1, 12, 28], "gaug": 12, "gaussbacksub": 21, "gaussian": [4, 5, 6, 8, 14, 18, 24, 27], "gaussian_point": 14, "gaussian_rbf": 8, "gave": [13, 30], "gavra": 27, "gbc": 27, "gca": [2, 6, 8, 13], "gd": [1, 29], "gd_clf": 10, "gdclassiffiercgain": 10, "gdclassiffierconfus": 10, "gdclassiffierroc": 10, "gdm": 13, "gdregress": 10, "ge": [1, 5, 7, 24, 28, 29], "gen_loss": 4, "gen_tap": 4, "gender": [0, 27], "genener": 4, "gener": [0, 1, 2, 3, 5, 6, 8, 10, 11, 12, 13, 14, 15, 16, 18, 21, 22, 24, 26, 28, 29, 30], "generaliz": 16, "generallay": 12, "generate_and_save_imag": 4, "generate_imag": 4, "generate_latent_point": 4, "generate_simple_clustering_dataset": 14, "generated_imag": 4, "generator_loss": 4, "generator_loss_list": 4, "generator_model": 4, "generator_optim": 4, "genom": 20, "geodes": 11, "geoff": 30, "geometr": [0, 13, 27], "geometri": 5, "georg": 26, "geotif": 6, "geq": [2, 5, 8, 9, 13, 28, 29, 30], "geron": [0, 26, 27], "get": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 15, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "get_dummi": 9, "get_paramet": 2, "get_split": 9, "get_yaxi": 8, "get_yticklabel": 6, "gh": 15, "gibb": [20, 27], "gif": 4, "gini": 10, "gini_index": 9, "ginvers": 13, "git": [0, 15, 20, 27], "giter": [13, 30], "github": [0, 20, 22, 23, 25, 26, 27, 28], "gitignor": 15, "gitlab": [0, 15, 20, 22, 27], "give": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 20, 22, 24, 27, 28, 29, 30], "given": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 21, 24, 27, 28, 29, 30], "global": [6, 7, 13, 29, 30], "glorot": 1, "gnew": 13, "go": [0, 1, 3, 5, 6, 8, 9, 11, 12, 13, 15, 16, 18, 27, 28, 29], "goal": [0, 7, 9, 27], "goe": [0, 1, 2, 5, 6, 13, 14, 15, 19, 21, 27, 28, 29, 30], "golden": 13, "gone": [5, 28, 29], "gong": 1, "good": [1, 3, 4, 5, 6, 9, 10, 11, 13, 15, 18, 20, 24, 26, 28, 29, 30], "goodfellow": [4, 26, 27, 28, 29], "googl": [1, 4, 20, 27], "got": [1, 6, 22], "gotten": 27, "gov": 6, "govern": 27, "gp": 26, "gpu": [1, 13, 20, 27], "grad": [2, 13, 30], "grad_analyt": 13, "grad_ol": 18, "grad_ridg": 18, "grade": [22, 23], "gradient": [0, 3, 4, 7, 8, 9, 12, 20, 27, 28], "gradient_desc": 30, "gradientboostingclassifi": 10, "gradientboostingregressor": 10, "gradients_of_discrimin": 4, "gradients_of_gener": 4, "gradienttap": 4, "gradual": [1, 14], "grai": [4, 6], "graph": [1, 9, 11, 12, 13, 16, 29], "graph_from_dot_data": 9, "graphic": [0, 1, 9, 15, 27], "grasp": 0, "gray_r": [1, 3], "grayscal": 3, "great": [5, 13, 15, 29, 30], "greater": [1, 7, 24, 28], "greatli": 13, "greedi": 9, "green": [0, 3, 9, 24], "grei": 4, "grid": [1, 3, 6, 7, 8, 12, 24, 28, 30], "grossli": [13, 29], "ground": [0, 27], "group": [0, 6, 7, 9, 14, 15, 20, 22, 23, 25, 27], "groupbi": [0, 27], "grow": [1, 3, 9, 10, 30], "growth": [0, 27], "gru": 4, "guarante": [0, 4, 13, 24, 27, 28, 29, 30], "guess": [1, 4, 10, 13, 14, 29, 30], "guestrin": 10, "gui": 15, "guid": 1, "h": [0, 1, 5, 6, 8, 13, 15, 19, 24, 25, 26, 27, 28, 29, 30], "h1": 2, "h_": [0, 13, 27, 29, 30], "h_0": 30, "h_1": [2, 13, 29], "h_2": [2, 13, 29], "h_m": 10, "h_t": 30, "ha": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "haanen": [25, 27], "habit": [0, 28], "had": [0, 1, 6, 7, 13, 27, 29, 30], "hadamard": [1, 12, 13, 30], "half": [1, 8, 9], "halv": 10, "hand": [0, 1, 2, 3, 5, 11, 12, 13, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30], "handi": [3, 22], "handl": [0, 1, 2, 5, 9, 11, 15, 18, 20, 28, 29, 30], "handle_unknown": 9, "handsid": 12, "handwrit": 12, "handwritten": [1, 5], "happen": [1, 2, 3, 4, 5, 6, 10, 13, 24, 28, 29, 30], "hard": [1, 7, 8, 10, 13, 29, 30], "hardcopi": [20, 27], "harder": [0, 1, 28], "harmon": 3, "hasn": [], "hassl": [0, 20, 27], "hast": [20, 27], "hasti": [0, 6, 16, 17, 19, 22, 26, 27, 28], "hat": [0, 1, 5, 6, 7, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 28, 29, 30], "have": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "haven": 1, "he": 7, "head": [4, 10, 24], "header": [0, 27], "heads_proba": 10, "health": [0, 28], "hear": [0, 13, 27, 30], "heart": [0, 7, 27], "heatmap": [0, 1, 3, 7, 17, 27], "heavili": 0, "heavisid": 1, "height": [1, 3, 6, 28], "held": [13, 30], "help": [0, 1, 4, 12, 13, 15, 16, 22, 27, 30], "helper": [4, 14], "henc": [0, 5, 6, 8, 9, 10, 12, 13, 27, 28, 29, 30], "henrik": [25, 27], "her": 7, "here": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "hereaft": [0, 8, 12, 27], "hermitian": 21, "hessenberg": 21, "hessian": [0, 2, 5, 13], "heterogen": [9, 10], "hi": 7, "hidden": [1, 3, 4, 12], "hidden_bia": 1, "hidden_bias_gradi": 1, "hidden_layer_s": [0, 1, 27], "hidden_neuron": 4, "hidden_weight": 1, "hidden_weights_gradi": 1, "hierarch": [5, 28, 29], "high": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 13, 14, 20, 21, 22, 27, 28, 29, 30], "higher": [0, 1, 3, 5, 6, 8, 13, 18, 22, 27, 28, 29, 30], "highest": [1, 2], "highli": [0, 3, 4, 10, 19, 20, 21, 26, 27, 28, 29, 30], "highwai": [], "hing": 8, "hint": [13, 15, 16, 28, 29], "hinton": 30, "hip": 20, "hire": 0, "hist": [4, 6, 7, 24], "histogram": [6, 7, 24], "histor": [7, 11], "histori": [3, 4, 12, 15, 30], "hitherto": 5, "hjorth": [25, 27, 28, 29, 30], "hobbi": 24, "hoc": [5, 28, 29], "hoff": 26, "hold": [1, 3, 6, 13, 14, 29, 30], "holder": [0, 27], "home": [], "homepag": [22, 27], "homework": [6, 13, 29, 30], "homogen": [1, 3, 9, 10, 13, 30], "honchar": 2, "hopefulli": [0, 11, 15, 24, 27, 30], "horizont": 11, "horlyk": [25, 27], "hors": [3, 7, 27], "hot": [1, 9], "hour": [1, 20, 23, 24, 25, 27], "how": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "howev": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 24, 27, 28, 29, 30], "hspace": [0, 4, 8, 10, 24, 27], "hstack": 1, "htf": 27, "html": [0, 16, 20, 22, 23, 25, 26, 27, 28, 29, 30], "http": [0, 3, 4, 6, 13, 15, 16, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30], "huang": [0, 27], "huber": [0, 27], "huge": [1, 3, 4, 20], "human": [0, 1, 3, 6, 9, 12, 28], "humid": 9, "hundr": 1, "hungri": 1, "hybrid": 23, "hydrogen": [0, 27], "hyperbol": [1, 4, 12], "hyperparam": 8, "hyperparamet": [3, 4, 5, 6, 9, 13, 18, 22, 28, 29, 30], "hyperplan": 11, "h\u00f8rlyk": [25, 27], "i": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30], "i0": [0, 27], "i1": [0, 6, 8, 12, 27, 28, 30], "i2": [0, 8, 12, 27], "i3": [0, 12, 27], "i5": [0, 27], "i_": [13, 29, 30], "i_1": [5, 6], "i_2": [5, 6], "i_t": 30, "ian": 26, "ic": [1, 22], "id": [7, 13, 29, 30], "ida": [25, 27], "idea": [0, 1, 2, 3, 4, 6, 9, 10, 12, 13, 21, 22, 28, 29, 30], "ideal": [0, 2, 6, 8, 13, 24, 27, 30], "idem": 6, "ident": [5, 6, 12, 13, 17, 18, 21, 28, 29], "identifi": [0, 1, 7, 9, 11, 12, 13, 14, 27, 28], "ieor": 24, "ifi": 26, "ifs": [20, 27], "ignor": [0, 1, 3, 9, 15, 28, 30], "ii": [21, 24], "iii": [21, 27], "ij": [0, 1, 3, 6, 8, 12, 14, 16, 21, 24, 27, 28, 30], "ik": [0, 21, 27, 28], "ill": 30, "illustr": [5, 7, 10, 12, 13, 14, 20, 27], "ilsvrc": 30, "im": 6, "imag": [1, 3, 4, 6, 9, 11, 12, 14, 26, 27], "image_at_epoch_": 4, "image_batch": 4, "image_height": 3, "image_path": [0, 6, 7, 9, 27], "image_width": 3, "imageio": 6, "images_from_seed_imag": 4, "imagin": 1, "immedi": [0, 3, 4, 6, 20, 27], "implement": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 22, 24, 27, 28, 29, 30], "impli": [3, 5, 6, 7, 13, 21, 28, 29, 30], "implicit": 3, "implicitli": [11, 24], "import": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 24, 30], "importantli": 3, "impos": [0, 6, 11, 12, 27], "imposs": [0, 5, 27, 28, 29], "impress": [0, 12, 27], "improv": [0, 4, 5, 9, 10, 11, 13, 15, 22, 28, 29], "impur": 9, "imread": 6, "imshow": [1, 3, 4, 6], "in3050": [26, 27], "in3310": 27, "in4080": [26, 27], "in4300": [26, 27], "in4310": 26, "in5400": 3, "in5550": 26, "in_out_neuron": 4, "inaccur": [13, 29], "inact": 12, "inadequ": [0, 27], "inappropri": 30, "inch": [6, 28], "includ": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 15, 16, 17, 18, 20, 24, 25, 26, 27, 28, 29], "include_bia": [6, 9], "incom": [12, 16], "incorrect": 1, "incoveni": 8, "increas": [0, 1, 3, 4, 5, 6, 9, 12, 13, 19, 22, 24, 27, 28, 30], "increasingli": 24, "increment": 30, "ind": 6, "inde": [0, 2, 4, 5, 6, 13, 27, 28, 29], "indefinit": 4, "independ": [0, 5, 6, 7, 8, 12, 13, 24, 27, 28, 29], "index": [0, 1, 3, 4, 10, 14, 20, 21, 22, 24, 26, 27], "index_col": [0, 27], "indic": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 16, 22, 27, 28], "indispens": 6, "individu": [1, 6, 7, 10, 12, 24, 27, 28, 30], "indu": [], "indx": 21, "indx1": 2, "indx2": 2, "indx3": 2, "ineffici": [3, 13], "inequ": [8, 13], "inequaltii": 29, "inertia": 13, "inf1000": [20, 27], "inf1100": [20, 27], "inf1100l": [20, 27], "inf1110": [20, 27], "inf3000": 27, "infeas": 9, "infer": [0, 1, 4, 6, 26, 27], "inferenc": 1, "infil": [0, 6, 7, 9, 27], "infin": [5, 6, 7, 11, 19, 28, 29], "infinit": [3, 30], "infinitesim": 24, "influenc": [6, 10, 18], "influenti": 1, "info": 27, "inform": [0, 1, 3, 4, 6, 9, 11, 12, 13, 14, 21, 22, 26, 27, 29, 30], "inforom": 15, "infrequ": 30, "infti": [3, 6, 13, 24, 29], "ingeni": [13, 29, 30], "ingredi": [0, 9, 27], "inher": 6, "inherit": [21, 27, 30], "initi": [0, 1, 2, 6, 10, 13, 14, 18, 21, 24, 27, 29, 30], "inject": 14, "inlin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 24, 27, 28, 29, 30], "inner": [0, 13, 28], "inp": 4, "inplac": 13, "input": [0, 1, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 22, 24, 27, 28, 29, 30], "input_dim": 1, "input_shap": [3, 4], "inputs": 1, "inputs_shuffl": [0, 1, 28], "insert": [3, 5, 6, 8, 10, 24, 28, 29], "insid": [4, 7], "insight": [0, 1, 5, 20, 27, 28, 29], "insist": [6, 13, 28, 30], "inspir": [0, 1, 12, 22, 27], "instabl": 2, "instal": [0, 1, 5, 6, 9, 15], "instanc": [0, 1, 2, 4, 6, 9, 11, 13, 16, 27, 28, 29], "instanti": 10, "instead": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 17, 21, 24, 27, 28, 30], "institut": 1, "instruct": [0, 1, 15], "int": [0, 1, 2, 3, 4, 5, 6, 11, 13, 14, 21, 24, 28, 30], "int32": 10, "int_": [3, 6, 24], "int_0": 24, "int_a": 24, "intak": [0, 28], "integ": [1, 2, 13, 14, 21, 24, 27], "integer_vector": 1, "integr": [3, 6, 24, 27], "intellig": [0, 14, 26, 27], "intend": 10, "intens": [1, 18], "intention": 14, "interact": [0, 6, 9, 12, 20, 22, 27], "intercept": [0, 6, 8, 11, 13, 16, 17, 18, 27, 28, 29, 30], "intercept_": [0, 6, 8, 9, 13, 27, 28, 30], "interchang": [5, 12, 21], "interconnect": 1, "interesit": 19, "interest": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 20, 22, 24, 27, 28, 29], "interfac": [0, 1, 15, 21, 28], "interior": [0, 9, 27], "intermedi": [21, 28], "intern": [1, 10, 12], "interpol": [1, 3, 4, 6, 12], "interpr": [5, 28, 29], "interpret": [0, 1, 6, 9, 10, 12, 13, 15, 16, 19, 21, 22, 24], "interv": [0, 3, 5, 6, 7, 13, 19, 24, 27, 28, 29], "intial": [13, 29], "intract": [0, 4, 28], "intrins": [3, 11, 21, 24, 27], "intro": [20, 26, 27], "introduc": [0, 1, 5, 6, 8, 10, 12, 21, 22, 24, 27, 29, 30], "introduct": [1, 2, 4, 13, 26, 28, 29, 30], "introductori": [0, 4, 21, 26, 27, 28], "intuit": [0, 5, 6, 8, 12, 13, 22, 27, 30], "inv": [0, 5, 13, 17, 27, 28, 29, 30], "invalu": [0, 13, 20, 27, 29], "invari": 1, "invd": 5, "inver": 8, "invers": [0, 3, 6, 13, 27, 28, 29, 30], "inverse_transform": 8, "invert": [0, 5, 7, 10, 13, 16, 18, 27, 30], "invh": [13, 30], "invok": 8, "involv": [0, 2, 6, 7, 11, 12, 27, 28, 30], "io": [0, 20, 22, 23, 25, 26, 27, 28], "ip": [0, 8, 24, 27], "ipca": 11, "ipynb": [20, 27], "ipython": [0, 5, 7, 9, 11, 14, 20, 22, 27, 28], "iq": 6, "iri": [8, 9], "irreduc": 6, "irrelev": [5, 28, 29], "irrespect": [0, 27], "irvin": 22, "iseffici": [], "isn": 5, "isnul": [], "isomap": 11, "issu": [1, 9, 15, 21, 30], "it_arrai": 13, "item": [0, 13, 27], "items": [21, 27], "iter": [1, 2, 4, 6, 8, 13, 14, 18, 22, 24, 29, 30], "its": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 20, 21, 22, 24, 27, 29, 30], "itself": [5, 6, 12, 19, 22, 24, 27, 28], "j": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 21, 22, 24, 26, 27, 28, 29, 30], "j1": 21, "j_": 6, "j_lasso_sk": 6, "j_ridge_sk": 6, "j_sk": 6, "jackknif": [6, 20, 27], "jacobian": [2, 13, 29], "jason": 4, "jax": [20, 27, 30], "jensen": [25, 27, 28, 29, 30], "jerom": [19, 22, 26], "ji": [12, 21], "jit": 13, "jj": [0, 5, 6, 27], "jk": [0, 1, 6, 12, 21, 27], "jl": [0, 27], "jm": 21, "jnp": 13, "job": [2, 8, 10, 15], "join": [0, 4, 6, 7, 9, 27], "joint": [4, 5], "judg": [13, 29], "judgement": 6, "julia": [20, 21, 22], "jump": 24, "junk": 4, "jupit": 27, "jupyt": [0, 15, 16, 20, 22, 26, 27], "just": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 24, 27, 28, 29, 30], "justif": 0, "justifi": [3, 10], "k": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 24, 25, 27, 28, 29, 30], "k0": 7, "k1": 7, "kaggl": [6, 22], "kappa_d": 24, "karl": [25, 27], "karush": 8, "katrin": [25, 27], "keep": [0, 1, 4, 5, 6, 11, 13, 14, 15, 18, 21, 22, 27, 28, 29, 30], "keepdim": [1, 6, 10, 21], "kei": [1, 3, 6, 12], "kept": [4, 6, 14], "kera": [0, 4, 20, 22, 27], "kernel": [0, 1, 3, 20, 27, 28], "kernel_regular": [1, 3], "kernel_s": 4, "kernelpca": 11, "kev": [0, 27], "kevin": [26, 27], "keyword": [18, 21, 27], "kfold": 6, "kg": 1, "ki": 21, "kick": [1, 13, 30], "kiener": 2, "kilomet": [6, 28], "kind": [0, 2, 3, 4, 8, 12, 13, 14, 27, 28], "kingma": 30, "kj": [6, 12, 21, 28, 30], "kjm": [20, 27], "kkt": 8, "kl": 24, "km": [12, 27], "kmean": 14, "kmeanspoint": 14, "kn_k": 14, "know": [0, 1, 2, 5, 6, 8, 13, 15, 16, 17, 19, 20, 27, 28, 29], "knowledg": [0, 20, 27], "known": [1, 3, 4, 5, 6, 7, 8, 9, 12, 18, 21, 22, 24, 26, 28, 30], "kondev": [0, 27], "kp": 24, "kpca": 11, "kroneck": 14, "kuhn": 8, "kvalsund": [25, 27], "kwown": [0, 27], "l": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 21, 22, 24, 27, 29], "l0": 7, "l1": [0, 1, 3, 7, 27], "l1_l2": [1, 3], "l1regl": 5, "l2": [1, 3], "l_": 21, "l_1": 7, "l_2": [7, 13, 29, 30], "l_j": 12, "la": 13, "la_i": 12, "la_k": 12, "lab": [20, 22, 27], "label": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 20, 21, 22, 24, 27, 28, 29, 30], "labelencod": [7, 10], "labels": [6, 8, 9], "labels_shuffl": [0, 1, 28], "laboratori": 23, "lack": [0, 27], "lagari": 2, "lagrang": [8, 11], "lam": 18, "lambda": [0, 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 17, 18, 19, 22, 24, 27, 28, 29, 30], "lambda_": 11, "lambda_0": 11, "lambda_1": [5, 8, 11, 28, 29], "lambda_2": [8, 11], "lambda_i": [8, 11], "lambda_iy_i": 8, "lambda_jy_iy_j": 8, "lambda_k": 8, "lambda_n": [5, 8, 28, 29], "lamda": 1, "land": 8, "landmark": 8, "landscap": [13, 18, 29, 30], "langl": [0, 6, 11, 24, 27, 28], "languag": [0, 1, 4, 8, 20, 21, 22, 26, 27], "lapack": [21, 27], "laplac": 5, "laptop": [15, 20], "larg": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 13, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30], "larger": [0, 3, 5, 6, 8, 10, 11, 13, 17, 24, 27, 28, 29, 30], "largest": [4, 8, 11], "lasso": [0, 7, 20, 27, 30], "lasso_sk": 6, "last": [0, 1, 3, 4, 5, 6, 7, 8, 12, 16, 17, 19, 21, 22, 24, 25, 27, 29], "latent": 4, "latent_dim": 4, "latent_point": 4, "latent_space_value_rang": 4, "later": [0, 1, 4, 7, 8, 12, 13, 14, 15, 20, 22, 27, 30], "latest": [4, 15, 20], "latest_checkpoint": 4, "latex": 27, "latter": [0, 3, 6, 7, 8, 11, 13, 21, 24, 27, 28, 29, 30], "lattic": 12, "law": 0, "layer": [0, 4, 13, 27, 30], "lbfg": [7, 9, 10], "lcc": [5, 6], "lda": 11, "ldot": [0, 6, 11, 22, 27], "le": [5, 7, 10, 13, 17, 24, 28, 29], "lead": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 21, 24, 27, 28, 29, 30], "leaf": 9, "leaki": 1, "leakyrelu": 4, "lear": [13, 29], "learn": [3, 4, 5, 6, 7, 8, 9, 10, 12, 21, 25, 26], "learnabl": 3, "learner": 10, "learnig": 27, "learning_r": [8, 10], "learning_rate_init": [0, 1, 27], "learning_schedul": [13, 30], "learnt": 22, "least": [0, 7, 8, 10, 11, 17, 18, 20, 21, 24], "leat": [13, 30], "leav": [0, 1, 3, 5, 6, 9, 11, 27, 29], "lectur": [0, 1, 5, 10, 11, 12, 13, 20, 21, 22, 23, 25, 26, 28], "lecturenot": [0, 20, 22, 26, 27], "left": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "leftarrow": [8, 12], "legend": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 15, 27, 28, 29, 30], "leinonen": 27, "len": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 16, 17, 21, 27, 28, 29, 30], "length": [0, 1, 3, 4, 8, 9, 13, 16, 20, 27, 28, 29, 30], "length_of_sequ": 4, "leq": [0, 5, 7, 8, 13, 14, 24, 27, 28, 29, 30], "less": [0, 1, 3, 4, 5, 6, 8, 9, 13, 20, 24, 27, 28, 29, 30], "lessen": 1, "let": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, 21, 24, 27, 28, 29, 30], "letter": [0, 16, 21, 24, 27, 28], "level": [0, 1, 5, 6, 9, 20, 21, 22, 23, 25, 27], "leverag": 30, "li": [8, 11], "lib": [], "liberti": 30, "liblinear": 10, "librari": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 21, 22, 24, 26, 28, 29, 30], "licens": [0, 1, 20, 22, 27], "lie": [0, 6, 11, 24, 27, 28], "life": [0, 1, 8, 12, 27], "lifetim": 13, "like": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 29, 30], "likelihood": [0, 1, 5, 9, 27, 28], "lim_": 24, "limit": [0, 5, 6, 8, 12, 21, 22, 27, 28], "lin_clf": 8, "lin_model": [], "lin_reg": 9, "linalg": [0, 2, 5, 6, 8, 11, 13, 17, 21, 24, 27, 28, 29, 30], "line": [0, 3, 6, 8, 11, 13, 15, 16, 27, 29, 30], "line1": 8, "line2": 8, "line3": 8, "line_model": 15, "line_ms": 15, "line_predict": 15, "linear": [1, 3, 5, 6, 7, 9, 10, 11, 12, 16, 17, 18, 19, 20, 22, 24, 30], "linear_model": [0, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 27, 28, 29, 30], "linear_regress": 6, "linearli": [5, 28, 29], "linearloc": [6, 13, 29, 30], "linearregress": [0, 6, 7, 9, 15, 16, 19, 27, 28, 30], "linearsvc": 8, "lineat": 29, "liner": [1, 3], "linerar": 10, "linewidth": [0, 2, 4, 6, 8, 9, 10], "link": [0, 4, 9, 12, 15, 20, 22, 23, 25, 27], "linlag": 5, "linpack": [21, 27], "linreg": [0, 27], "linspac": [0, 2, 3, 4, 6, 8, 9, 10, 13, 16, 17, 19, 21, 24, 27, 28, 30], "linu": 4, "linux": [0, 1, 20, 22, 27], "liquid": [0, 27], "list": [1, 2, 3, 4, 9, 15, 20, 22, 27, 30], "listedcolormap": [9, 10], "literatur": [1, 7, 14, 26], "littl": [1, 3, 9, 12, 30], "live": [8, 16], "ll": [0, 18, 24, 27, 28], "lle": [0, 28], "lloyd": [4, 14], "lmb": [0, 2, 5, 6, 28, 29, 30], "lmbd": [0, 1, 3, 27], "lmbd_val": [0, 1, 3, 27], "lmbda": [13, 29, 30], "ln": [1, 13, 29], "load": [1, 4, 6, 7, 9, 10], "load_boston": [], "load_breast_canc": [1, 7, 9, 10, 11], "load_data": [3, 4], "load_digit": [1, 3], "load_iri": [8, 9], "loc": [3, 6, 7, 8, 9, 10, 27], "local": [0, 1, 3, 7, 12, 13, 15, 28, 29, 30], "locat": [2, 3, 8, 15], "log": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 13, 15, 21, 22, 27], "log10": [0, 5, 6, 28, 29, 30], "log_": [0, 27], "log_clf": 10, "logarithm": [0, 5, 7, 17, 21, 27], "logbook": 22, "logic": [0, 1, 9, 27], "login": 15, "logist": [0, 1, 2, 8, 9, 10, 11, 12, 13, 20, 28, 29, 30], "logisticregress": [7, 9, 10, 11], "logit": 7, "logreg": [7, 9, 10, 11], "logspac": [0, 1, 3, 5, 6, 27, 28, 29, 30], "long": [0, 1, 3, 4, 12, 13, 27, 29, 30], "longer": [2, 3, 8, 10, 14, 21, 24, 27, 30], "loocv": 6, "look": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 21, 22, 24, 27, 28, 29, 30], "loop": [1, 4, 6, 10, 12, 14, 16, 17, 18, 20, 21, 27], "lose": 1, "loss": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 13, 18, 21, 22, 27], "loss_fil": 4, "lossfil": 4, "lost": 4, "lot": [1, 4, 6, 16, 30], "low": [0, 6, 9, 10, 11, 22, 27, 28], "lower": [0, 1, 3, 6, 9, 10, 16, 21, 28], "lowercas": [21, 27], "lowest": [9, 13, 24, 30], "lr": [1, 3, 4, 10], "lstat": [], "lstm": 4, "lstm_2layer": 4, "lstsq": [0, 27, 28], "lt": 6, "lu": [0, 5, 27, 28, 29], "lubksb": 21, "luckili": 2, "ludcmp": 21, "lux": 21, "lvert": 1, "lw": [0, 27], "m": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 15, 21, 24, 25, 26, 27, 28, 29, 30], "m_": [9, 12], "m_0": 30, "m_1": 14, "m_h": [0, 27], "m_k": 14, "m_l": 12, "m_n": [0, 27], "m_p": [0, 27], "m_t": [13, 30], "ma": 11, "machin": [1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 15, 16, 21, 26, 28], "machinelearn": [0, 6, 16, 20, 22, 23, 25, 26, 27, 28, 29], "mackai": 26, "made": [0, 1, 3, 4, 5, 6, 7, 9, 11, 12, 22, 27, 28], "mae": [0, 27], "magic": 4, "magnitud": [1, 6, 7, 13, 28, 30], "mai": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 19, 20, 21, 22, 24, 27, 28, 29, 30], "mail": [23, 25], "main": [0, 1, 3, 4, 5, 6, 7, 9, 21, 22, 26, 28, 29, 30], "mainli": [0, 5, 6, 7, 9, 27, 28], "maintain": [6, 30], "major": [1, 6, 9, 10, 13, 21, 27, 29, 30], "make": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 18, 20, 21, 22, 24, 26, 27, 29, 30], "make_axes_locat": 6, "make_moon": [8, 9, 10], "make_pipelin": [0, 6, 10, 28], "makedir": [0, 6, 7, 9, 27], "malcondit": 21, "malign": [1, 7, 9], "mammographi": 5, "manag": [0, 2, 3, 15, 20, 22, 27], "mandatori": [25, 27], "mani": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30], "manifold": 11, "manner": 3, "manual": [6, 28, 30], "map": [0, 1, 2, 6, 7, 8, 11, 12, 14, 24, 27], "marc": 28, "margin": [0, 5, 8], "marit": [0, 27], "mark": 27, "marker": [7, 21, 27], "markov": [20, 27], "marsaglia": 24, "mass": [0, 1, 5, 13, 28, 29], "massag": [0, 27], "masses2016": [0, 27], "masses2016ol": [0, 27], "masses2016tre": 0, "masseval2016": [0, 27], "master": [23, 25], "mat": [20, 27], "mat1100": [20, 27], "mat1110": [20, 27], "mat1120": [20, 27], "match": [1, 4, 5, 13, 14, 15, 28, 29, 30], "materi": [4, 5, 7, 13, 15, 21, 23, 25], "math": [3, 7, 12, 13, 21, 24, 26, 27, 30], "mathbb": [0, 4, 5, 6, 7, 8, 11, 12, 13, 14, 17, 19, 21, 22, 24, 27, 28, 29, 30], "mathbf": [0, 5, 6, 7, 8, 13, 19, 21, 22, 27, 28, 29, 30], "mathcal": [1, 5, 6, 7, 13, 22], "matheemat": 3, "mathemat": [0, 6, 11, 12, 13, 20, 21, 24, 26, 27, 30], "mathemati": 27, "mathrm": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 22, 24, 27, 28, 29, 30], "matmul": [1, 2, 5], "matnat": 26, "matplotlib": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 20, 21, 22, 24, 27, 28, 29, 30], "matric": [0, 1, 3, 4, 6, 7, 8, 11, 13, 16, 17, 20, 28, 29], "matrix": [0, 2, 3, 4, 6, 7, 8, 10, 13, 17, 18, 19, 22, 24], "matshow": 1, "matter": [2, 3, 13, 28, 29, 30], "max": [0, 1, 2, 3, 4, 9, 10, 12, 13, 25, 27, 29, 30], "max_depth": [0, 9, 10], "max_diff": 2, "max_diff1": 2, "max_diff2": 2, "max_it": [0, 1, 8, 13, 27], "max_iter": 14, "max_leaf_nod": 10, "max_sampl": 10, "maxdegre": [0, 6, 10, 28], "maxdepth": 10, "maxim": [1, 4, 5, 7, 8, 11], "maximum": [0, 2, 3, 5, 7, 8, 9, 10, 13, 14, 27, 28, 29, 30], "maxpolydegre": [5, 6, 28, 29, 30], "maxpooling2d": 3, "mbox": [5, 6, 28, 29], "mcculloch": 12, "md": 11, "mdoel": 4, "mean": [1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 27, 30], "mean_absolute_error": [0, 27], "mean_divisor": 14, "mean_i": 24, "mean_matrix": 14, "mean_squared_error": [0, 4, 6, 7, 10, 15, 19, 27, 28], "mean_squared_log_error": [0, 27], "mean_vector": 14, "mean_x": 24, "meaning": [0, 4, 7, 27], "meansquarederror": [0, 27], "meant": [3, 7, 10, 13], "meanwhil": 30, "measur": [0, 1, 2, 5, 6, 9, 11, 12, 14, 16, 18, 19, 22, 24, 27, 28, 30], "mechan": [0, 4, 24, 27, 30], "median": [0, 27, 28, 30], "medicin": 12, "medium": [4, 8, 13], "medv": [], "meet": [0, 25], "mehta": [0, 27, 28, 29], "memori": [3, 4, 11, 12, 13, 18, 21, 30], "mention": [0, 12, 13, 22, 24, 27, 29, 30], "mere": [0, 22], "meshgrid": [2, 5, 6, 8, 9, 10, 11], "mess": 15, "messag": [5, 13], "messi": 2, "met": [0, 3, 8, 28], "meteorolog": 9, "meter": [6, 28], "method": [0, 1, 2, 3, 4, 5, 7, 8, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 24, 26, 28], "metion": 6, "metric": [0, 1, 3, 6, 7, 9, 10, 14, 15, 19, 27, 28], "metropoli": [20, 27], "mev": [0, 24, 27], "mgd": [13, 30], "mglearn": [20, 27], "mgrid": 13, "mhjensen": [], "mi": 10, "mia": [25, 27], "microsoft": 26, "mid": 1, "midel": 4, "midnight": 15, "midpoint": 9, "might": [0, 1, 2, 4, 6, 9, 13, 15, 17, 18, 28, 29, 30], "migth": 17, "mild": 9, "millimet": [6, 28], "million": [0, 27, 28, 30], "mimic": 12, "min": [0, 2, 5, 8, 9, 29], "min_": [0, 2, 5, 14, 17, 27, 28, 29], "min_samples_leaf": 9, "mind": [0, 6, 13, 15, 18, 27, 28, 29, 30], "mindboard": 4, "mine": [20, 27], "mini": [1, 11, 12, 13, 29], "minibatch": [1, 11, 13], "minibathc": [13, 30], "miniforge3": [], "minim": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 28, 29, 30], "minima": [0, 1, 7, 13, 27, 29, 30], "minimum": [0, 1, 2, 6, 8, 9, 11, 13, 28, 29, 30], "minmaxscal": [0, 28, 30], "minor": 24, "minst": 1, "minu": 7, "mirjalili": 27, "mirror": 9, "misc": 6, "misclassif": [8, 9, 10], "misclassifi": [8, 10], "miser": 0, "mismatch": 1, "miss": [7, 10], "mistak": 4, "mit": 26, "mix": [1, 2, 27], "mixtur": [13, 30], "mk": [9, 21], "mkdir": [0, 6, 7, 9, 27], "ml": [0, 1, 10, 13, 21, 22, 28, 29, 30], "mlab": 24, "mle": [5, 7], "mlp": 1, "mlpclassifi": 1, "mlpregressor": [0, 27], "mm": 21, "mml": 28, "mn": [12, 24], "mnist": [1, 11], "mod": 24, "mode": [23, 25, 27], "model": [2, 3, 5, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 20, 22, 24, 26, 28, 29, 30], "model_select": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "moder": [10, 30], "modern": [0, 6, 7, 20, 27], "modif": [2, 12, 13], "modifi": [0, 1, 3, 5, 7, 8, 10, 12, 13, 27, 28, 29, 30], "modul": [0, 16, 21, 27], "modular": 24, "modulo": 24, "moe": [11, 28], "moment": [5, 6, 13, 24], "mondai": [25, 27], "monitor": [13, 30], "monoton": [5, 12, 24], "mont": [0, 6, 20, 24, 26, 27], "montli": 16, "moor": [5, 6], "more": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 24], "moreov": [0, 3], "morten": [25, 27, 28, 29, 30], "mortenhj": 27, "most": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 20, 22, 24, 27, 28, 29, 30], "mostli": [1, 11, 18], "motion": [0, 13], "motiv": [1, 4], "move": [0, 4, 5, 6, 7, 9, 12, 13, 14, 15, 16, 22, 24, 28, 29], "mpl": [7, 27], "mpl_toolkit": [2, 6, 13, 29, 30], "mplot3d": [2, 6, 13, 29, 30], "mplregressor": 1, "mse": [0, 4, 5, 6, 9, 10, 15, 16, 17, 19, 22, 27, 28, 29, 30], "mse_simpletre": 10, "mselassopredict": [5, 29], "mselassotrain": [5, 29], "mseownridgepredict": [6, 28, 29, 30], "msepredict": [5, 29], "mseridgepredict": [0, 5, 6, 28, 29, 30], "msetrain": [5, 29], "msle": [0, 27], "mt": [7, 12], "mu": [0, 6, 11, 13, 24, 27], "mu0": 24, "mu1": 24, "mu2": 24, "mu_": [6, 24, 28, 30], "mu_i": [6, 28, 30], "mu_n": 11, "mu_x": 24, "much": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 21, 22, 24, 27, 28, 29, 30], "multi": [0, 1, 3, 7, 20, 27], "multiclass": [1, 7], "multidimension": [11, 12, 27], "multilay": 1, "multinomi": 7, "multipl": [2, 4, 5, 6, 7, 12, 13, 15, 24, 28, 29], "multipli": [3, 5, 6, 11, 13, 18, 21, 24, 28, 29, 30], "multiplum": 8, "multivari": [0, 2, 10, 11, 20, 24, 27], "multivariate_norm": [11, 14], "multpli": 16, "murphi": [11, 26, 27], "must": [1, 2, 5, 6, 8, 10, 12, 13, 14, 15, 24, 28, 29, 30], "mutat": 7, "mutual": [1, 3, 6, 13], "mx_": 24, "my": 27, "myenv": [], "myriad": [0, 20, 27], "mz1": 24, "mz2": 24, "m\u00f8svatn": 6, "n": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "n1": 21, "n2": 21, "n_": [1, 2, 3, 8, 12, 24], "n_0": [12, 24], "n_boostrap": [6, 10], "n_bootstrap": 6, "n_categori": [1, 3], "n_cluster": 14, "n_compon": 11, "n_epoch": [13, 30], "n_estim": 10, "n_examples_to_gener": 4, "n_featur": [1, 18], "n_filter": 3, "n_hidden": 2, "n_hidden_neuron": [0, 1, 27], "n_i": 24, "n_input": [0, 1, 3, 28], "n_instanc": 9, "n_iter": 30, "n_job": 10, "n_k": 14, "n_l": [12, 24], "n_layer": 1, "n_m": 9, "n_neuron": 1, "n_neurons_connect": 3, "n_neurons_layer1": 1, "n_neurons_layer2": 1, "n_point": 14, "n_sampl": [6, 8, 9, 10, 14, 18], "n_split": 6, "n_step": 4, "n_t": 2, "n_x": 2, "nabla": [1, 13, 29, 30], "nabla_": [2, 13, 29, 30], "nabla_w": 13, "nag": 13, "naimi": [0, 27], "naiv": 7, "naive_kmean": 14, "name": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 18, 20, 21, 22, 24, 25, 27, 28, 29], "narrow": [13, 30], "nation": [1, 5], "nativ": [20, 27], "natur": [0, 1, 4, 8, 9, 12, 13, 22, 24, 26, 27, 29, 30], "navier": 12, "navig": 15, "nb": 24, "nb_": 21, "nbconvert": 27, "nd": 14, "ndarrai": 6, "ne": [9, 10, 21, 24, 28, 29], "nearest": [1, 3, 6, 11], "nearli": [13, 29], "neat": 27, "neccesari": 6, "necess": 2, "necessari": [0, 1, 3, 4, 8, 14, 18, 27], "necessarili": [0, 4, 11, 24, 27], "necesserali": 5, "neck": 7, "need": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 24, 28, 29, 30], "neg": [0, 1, 3, 5, 6, 7, 10, 13, 21, 24, 27, 29], "neg_mean_squared_error": 6, "neglect": [24, 30], "neglig": 24, "neighbor": [3, 6, 11], "neither": [4, 13], "neq": [13, 14, 24, 29], "nervou": 12, "nest": [9, 12], "nesterov": 13, "net": [2, 4, 12], "netlib": [21, 27], "network": [0, 9, 13, 20, 26, 28, 30], "neural": [0, 13, 20, 26, 28, 30], "neural_network": [0, 1, 2, 27], "neuralnetwork": 1, "neuron": [1, 2, 3, 4, 12], "neutral": [0, 27], "neutron": [0, 27], "never": [1, 4, 6, 9, 24], "new": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 21, 27, 28, 29, 30], "new_chang": [13, 30], "new_hobbit": 27, "newaxi": [0, 3, 6, 9], "newli": [0, 27], "newton": [1, 7, 8, 13, 24], "next": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 27, 28, 29], "next_guess": 13, "next_input": 4, "ng": 1, "ni": 14, "nice": [0, 1, 5, 11, 27, 28, 29], "nicer": [18, 30], "niter": [13, 29, 30], "nitric": [], "nlambda": [0, 5, 6, 28, 29, 30], "nlp": 26, "nm": 24, "nm_n": [0, 27], "nmse": 6, "nn": [2, 5, 6, 12, 21, 27], "nn_model": 1, "nnmin": 2, "node": [1, 3, 9, 10, 12], "nois": [0, 4, 5, 6, 8, 9, 10, 13, 18, 19, 22, 27, 28, 29, 30], "noise_dimens": 4, "noisi": [1, 6, 22, 30], "non": [0, 1, 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 21, 24, 27, 28, 29, 30], "nondifferenti": 30, "none": [0, 1, 2, 4, 5, 9, 10, 13, 24, 27, 28], "nonlinear": [3, 6, 8, 9, 11, 12], "nonneg": [6, 9, 13, 29], "nonparametr": 6, "nonsens": 24, "nonsingular": 21, "nonumb": [3, 7, 8, 13, 21], "nor": [1, 4, 13], "norm": [0, 1, 5, 6, 8, 11, 13, 18, 27, 28, 29, 30], "normal": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "normali": [21, 27], "norwai": [6, 22, 27, 29, 30], "notat": [0, 2, 5, 6, 13, 14, 24, 27, 28, 29], "note": [0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 24, 26, 27, 30], "notebook": [0, 1, 3, 9, 15, 16, 20, 22, 27], "noth": [1, 2, 5, 8, 12, 14, 24, 28, 29], "notic": [4, 5, 12, 13, 21, 24, 27], "notion": 3, "novel": [3, 6, 10, 27], "novemb": [1, 25, 27], "now": [0, 2, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 19, 20, 21, 22, 24, 27, 28], "nowadai": [0, 1, 3, 9, 20, 27], "nox": [], "np": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 24, 27, 28, 29, 30], "npr": 2, "nsampl": 6, "nt": 2, "nu": 24, "nuclear": [5, 28, 29], "nuclei": [0, 24, 27], "nucleon": [0, 27], "nucleu": [0, 27], "num": 4, "num_coordin": 2, "num_hidden_neuron": 2, "num_it": [2, 18], "num_neuron": 2, "num_neurons_hidden": 2, "num_point": 2, "num_tre": 10, "num_valu": 2, "number": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 23, 25, 27, 29], "numberid": 7, "numberparamet": 3, "numer": [0, 5, 6, 9, 10, 11, 12, 13, 20, 21, 26, 27, 28, 29, 30], "numpi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 24, 28, 29, 30], "nunmpi": [5, 28], "nve_frngahw": 29, "nx": 2, "ny": 24, "o": [0, 1, 4, 5, 6, 7, 8, 9, 11, 21, 25, 26, 27, 28, 29], "obei": [6, 11, 13, 28, 30], "object": [0, 1, 4, 8, 10, 15, 19, 21, 27, 30], "obliqu": [5, 28, 29], "observ": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 24, 27, 29, 30], "obtain": [0, 1, 5, 6, 7, 8, 9, 10, 12, 13, 14, 17, 21, 22, 24, 27, 28, 29, 30], "obviou": [5, 6, 11, 24, 28, 29], "obviouli": 27, "obvious": [0, 4, 5, 6, 21, 27], "oc": [28, 29], "occupi": [], "occur": [0, 6, 8, 9, 21, 24, 27], "octob": [25, 27], "od": 0, "odd": [0, 3, 7, 27, 28, 30], "odenum": 2, "odesi": 2, "oen": 0, "off": [1, 3, 4, 5, 9, 13, 24], "offer": [6, 11, 20, 21, 23, 25, 27], "offic": [25, 27], "offici": [23, 27], "often": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 22, 24, 27, 28, 29, 30], "ofter": [21, 27], "ol": [0, 13, 17, 19, 28, 30], "old": [1, 5, 10, 13, 15, 18], "ols_paramet": 16, "ols_sk": 6, "ols_svd": 6, "olsbeta": 29, "olstheta": [0, 5], "omega": [2, 3, 6], "omega_0": 3, "omit": [0, 5, 27, 28, 29], "onc": [1, 6, 9, 11, 13], "one": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 19, 20, 21, 22, 24, 25, 27, 28, 30], "onehot": 1, "onehot_vector": 1, "onehotencod": 9, "ones": [0, 2, 5, 6, 8, 9, 10, 11, 13, 16, 18, 21, 22, 27, 28, 29, 30], "ones_lik": 4, "ong": 28, "onl": 3, "onli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 21, 22, 24, 27, 28, 29, 30], "onlin": [11, 15, 23], "onto": [5, 11, 28, 29], "open": [0, 1, 4, 6, 7, 9, 15, 20, 22, 23, 25, 27], "oper": [0, 1, 3, 5, 6, 10, 11, 12, 13, 15, 16, 20, 24, 27, 28, 29, 30], "operation": 24, "oplu": 24, "opmiz": [13, 30], "opportun": 0, "oppos": [6, 13], "opposit": [1, 5, 8, 28, 29], "opt": [1, 5, 22, 27, 29], "optim": [0, 2, 3, 4, 5, 6, 7, 9, 10, 11, 14, 16, 17, 19, 22], "optimis": [1, 3], "option": [0, 1, 3, 5, 6, 8, 11, 15, 18, 21, 28, 30], "optmiz": [1, 8, 13, 28], "oral": 27, "orang": 0, "order": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 15, 19, 21, 22, 24, 27, 28, 29], "ordinari": [0, 2, 3, 7, 11, 13, 17, 18, 20], "oreilli": [26, 27], "org": [0, 3, 4, 16, 20, 21, 22, 26, 27, 28, 29, 30], "organ": [6, 7, 10, 21], "orient": [1, 5, 24, 28, 29], "origin": [0, 3, 5, 6, 8, 11, 12, 13, 15, 21, 27, 28, 29, 30], "orthogn": [5, 28, 29], "orthogon": [0, 5, 6, 8, 11, 13, 21, 27, 28, 29], "orthonorm": [5, 28, 29], "os": [25, 27], "oscar": 1, "oscil": [3, 13, 30], "oskar": 27, "oskarlei": 27, "osl": 18, "oslo": [0, 20, 22, 23, 25, 27, 28, 29, 30], "osx": [0, 20, 22, 27], "other": [0, 1, 2, 3, 5, 6, 7, 8, 10, 13, 14, 16, 20, 23, 24, 25, 26, 28, 29, 30], "otherwis": [0, 1, 4, 7, 13, 21, 27, 30], "ouput": [5, 7, 12], "our": [1, 2, 3, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 18, 19, 20, 21, 24, 30], "ourmodel": 0, "ourselv": [0, 5, 6, 8, 11, 13, 27, 28, 29], "out": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 30], "out_fil": 9, "outcom": [0, 7, 9, 10, 12, 24, 28], "outdoor": 9, "outer": [6, 12, 13], "outfil": 4, "outlier": [0, 8, 27, 28, 30], "outlin": [6, 10, 11], "outlook": 9, "outperform": [10, 30], "output": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 21, 22, 24, 27, 28, 29, 30], "output_bia": 1, "output_bias_gradi": 1, "output_shap": 4, "output_weight": 1, "output_weights_gradi": 1, "outputlayer1": 12, "outputlayer2": 12, "outsid": 4, "over": [0, 1, 3, 4, 5, 6, 9, 10, 12, 13, 15, 16, 21, 22, 27, 28, 29, 30], "over1": 13, "overal": [1, 10, 30], "overcast": 9, "overcom": [12, 13], "overdetermin": [0, 27], "overfit": [0, 1, 3, 6, 9, 10, 13, 30], "overflow": 5, "overhead": 12, "overlap": [3, 7, 8, 9], "overlin": [0, 5, 6, 9, 10, 11, 14, 21, 27, 28, 30], "overshoot": 30, "overst": 0, "overtrain": 4, "overview": 3, "own": [4, 5, 6, 8, 12, 13, 16, 18, 20, 21, 29, 30], "owner": [], "ownmsepredict": 0, "ownmsetrain": 0, "ownridgebeta": 28, "ownridgetheta": [0, 6, 28, 29, 30], "ownypredictridg": 0, "ownytilderidg": 0, "oxid": [], "p": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 24, 27, 28, 29, 30], "p0": 2, "p1": 2, "p_": [2, 4, 8, 9], "p_hidden": 2, "p_i": [5, 24], "p_j": 24, "p_n": 24, "p_output": 2, "p_x": 24, "pack": [0, 27], "packag": [0, 1, 3, 4, 5, 8, 11, 13, 15, 20, 22, 24, 28, 29, 30], "packtpub": 27, "packtpublish": 27, "pad": [3, 4], "page": [0, 20, 27, 29, 30], "pai": [0, 1, 9, 13, 15, 30], "pair": [0, 2, 3, 9, 20, 24, 27], "paltform": 15, "panda": [0, 4, 5, 6, 7, 9, 11, 20, 22, 29, 30], "panel": 27, "paper": [1, 30], "paradigm": [0, 27], "parallel": [10, 13, 20, 21, 27], "param": 2, "paramat": 2, "paramet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, 18, 19, 22, 24, 29, 30], "parameter": [0, 6, 10, 27, 28], "parametr": [0, 6, 27, 28], "paramt": [3, 5], "part": [0, 1, 3, 5, 6, 10, 17, 19, 21, 23, 24, 25, 27, 28], "partial": [0, 1, 5, 6, 7, 8, 10, 11, 12, 13, 16, 24, 27, 28, 29, 30], "particip": [15, 20, 23, 25, 27], "particl": [0, 4, 13, 24, 27], "particular": [0, 1, 2, 3, 5, 6, 9, 10, 11, 12, 13, 16, 22, 24, 26, 27, 28, 29, 30], "particularli": [5, 6, 8, 11, 13, 24, 28, 29, 30], "partit": [1, 4, 9], "partli": [6, 27], "partner": 15, "pass": [2, 3, 12, 14], "password": 22, "past": [10, 24, 30], "patch": [6, 24], "path": [0, 4, 6, 7, 9, 20, 27], "pathcollect": 17, "patient": 7, "patter": 4, "pattern": [0, 3, 4, 12, 26, 27], "pauli": [0, 27], "pc": [11, 15, 20], "pca": [0, 7, 20, 27, 28], "pd": [0, 4, 5, 6, 7, 9, 11, 27, 28, 29, 30], "pde": 2, "pdf": [0, 3, 4, 5, 6, 9, 15, 16, 22, 26, 27], "pedagog": [0, 27, 28], "penal": [6, 18, 28, 30], "penalti": [6, 13, 18, 22, 28, 30], "penros": [5, 6], "pentagon": [13, 29], "peopl": [1, 9, 13, 20, 30], "per": [0, 1, 6, 23, 25, 27, 30], "percentag": [10, 11, 25], "perceptron": [0, 1, 7, 27], "peregrin": 27, "perfect": [0, 1, 13, 27, 30], "perfectli": [4, 6], "perform": [0, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 14, 16, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "performac": 4, "perhap": [0, 5, 13, 27, 28, 29], "perimet": 1, "period": [1, 4, 24], "permiss": 15, "permut": 11, "persist": 13, "person": [5, 6, 7, 16, 23, 25, 27, 28], "perspect": 26, "pertin": [12, 27], "petal": [8, 9], "peter": [26, 28], "phantom": 24, "phase": [6, 12], "phenomena": 24, "phi": 8, "phi_k": 8, "philosophi": 13, "phone": [25, 27], "photo": [4, 27], "php": 22, "phrase": [0, 27], "physic": [0, 1, 4, 7, 12, 13, 24, 25, 26, 27, 28, 29, 30], "pi": [2, 3, 5, 6, 7, 9, 12, 13, 24], "pick": [1, 9, 10, 11, 13, 14, 30], "pickl": 1, "pictur": [0, 27], "pie": [20, 27], "piec": [11, 14], "pillow": [0, 20, 22, 27], "pinv": [5, 6, 13, 22, 28, 29, 30], "pip": [0, 1, 15, 20, 22, 27], "pip3": [0, 1, 22, 27], "pipelin": [0, 6, 8, 10, 28], "pippin": 27, "pit": 4, "pitfal": [6, 28], "pitt": 12, "pixel": [1, 3, 4, 27], "pixel_height": [1, 3], "pixel_width": [1, 3], "place": [0, 4, 6, 8, 13, 15, 21, 22, 27, 29], "plai": [0, 3, 4, 5, 6, 8, 11, 18, 20, 22, 27, 28, 29], "plain": [8, 10, 12, 13, 14, 29, 30], "plan": [6, 9, 25, 26, 27], "plane": [8, 9], "plateau": [5, 29], "platform": [20, 27], "plausibl": 12, "pleas": [13, 22, 25, 27], "plenti": 1, "plethora": [3, 12], "plot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 21, 22, 24, 27, 28, 29, 30], "plot_all_sc": [22, 28], "plot_confusion_matrix": [7, 10], "plot_count": 6, "plot_cumulative_gain": [7, 10], "plot_data": 1, "plot_dataset": 8, "plot_decision_boundari": [9, 10], "plot_import": 10, "plot_max": 4, "plot_min": 4, "plot_model": 4, "plot_numb": 4, "plot_predict": 8, "plot_regression_predict": 9, "plot_result": 4, "plot_roc": [7, 10], "plot_surfac": [2, 6, 13], "plot_train": 9, "plot_tre": [9, 10], "plt": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 24, 27, 28, 29, 30], "plu": [0, 3, 5, 7, 18, 27, 28], "pm": 8, "pmatrix": 2, "pml": 26, "pn": 3, "png": [0, 4, 6, 7, 9, 27], "point": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 21, 22, 24, 25, 27, 28, 29, 30], "point_1": 4, "point_2": 4, "poisson": [20, 24, 27], "poli": [6, 8], "poly100_kernel_svm_clf": 8, "poly3": 0, "poly3_plot": 0, "poly_featur": [8, 9, 15], "poly_features10": 9, "poly_fit": 9, "poly_fit10": 9, "poly_kernel_svm_clf": 8, "poly_model": 15, "poly_ms": 15, "poly_predict": 15, "polydegre": [0, 5, 6, 10, 28], "polygon": [13, 29], "polym": 12, "polymi": 22, "polynomi": [0, 5, 6, 7, 8, 9, 10, 11, 15, 17, 19, 22, 27, 28], "polynomial_featur": [6, 15, 16, 17], "polynomial_svm_clf": 8, "polynomialfeatur": [0, 6, 8, 9, 15, 16, 19, 28], "polytrop": [0, 6], "pool": 3, "pool_siz": 3, "poor": [1, 13, 29, 30], "poorli": [0, 28], "popul": [0, 5, 27, 28], "popular": [0, 1, 3, 6, 7, 8, 9, 11, 12, 15, 20, 21, 22, 24, 28], "popularli": [0, 27], "portabl": 10, "portion": [11, 13, 30], "pose": [0, 4, 5, 6, 11, 24, 27], "posit": [0, 1, 2, 3, 5, 7, 8, 10, 11, 13, 14, 21, 24, 27, 28, 29, 30], "possibl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20, 21, 22, 24, 25, 27, 28, 29, 30], "possibli": [6, 8, 13, 22], "posterior": 5, "postpon": [0, 28], "postscript": 22, "postul": 5, "potenti": [0, 3, 5, 6, 12, 13, 28, 30], "pott": 12, "power": [0, 1, 5, 6, 8, 9, 12, 13, 27, 28, 29, 30], "pp": [5, 6, 19], "practic": [0, 5, 6, 7, 8, 16, 18, 22, 24, 28], "practition": [0, 1, 3, 27], "pre": 27, "preced": [1, 11, 12, 24], "preceed": 4, "preceq": 8, "precis": [0, 2, 5, 11, 13, 21, 22, 24, 27, 28], "pred": 6, "predicit": 0, "predict": [0, 1, 5, 6, 7, 8, 9, 10, 15, 16, 17, 19, 20, 22, 26, 27, 28, 29, 30], "predict_prob": 1, "predict_proba": [7, 10], "predictor": [0, 5, 6, 7, 9, 10, 11, 27, 28, 30], "prefer": [0, 1, 6, 8, 9, 11, 13, 15, 20, 22, 27], "prepar": [0, 6, 21, 22, 27, 28], "preprocess": [0, 4, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18, 19, 22], "prerequisit": 0, "prescript": 22, "presenc": 13, "present": [0, 5, 6, 7, 9, 12, 13, 21, 22, 24, 27, 28, 29, 30], "preserv": [3, 11, 21], "press": [13, 15, 26, 29], "pretrain": [1, 4], "pretti": [0, 4, 8, 9, 20, 22, 27], "prev_centroid": 14, "prevent": [13, 24, 30], "previou": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 21, 22, 24, 28, 29, 30], "previous": [2, 3, 9, 10, 24], "price": [0, 4, 9, 13, 30], "primal": 8, "primari": [0, 7, 27], "prime": 24, "princip": [0, 5, 7, 20, 27, 28, 29], "principl": [0, 6, 7, 8, 14, 27], "print": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 21, 24, 27, 28, 29, 30], "print_funct": [8, 9], "printout": [0, 27], "prior": [0, 5, 6, 27], "privat": 0, "prob": [1, 24], "probabilist": [0, 26, 27, 28], "probabl": [0, 1, 3, 4, 6, 7, 10, 13, 20, 27, 28, 30], "problem": [0, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 19, 20, 21, 22, 24], "probml": 26, "proce": [0, 5, 6, 7, 8, 9, 10, 11, 13, 21, 27, 28], "procedur": [2, 4, 5, 6, 8, 10, 11, 13, 28, 29, 30], "proceed": 21, "process": [0, 2, 4, 6, 9, 10, 12, 13, 20, 21, 22, 24, 26, 27, 29, 30], "prod": 26, "prod_": [1, 5, 7], "produc": [0, 3, 4, 5, 6, 9, 10, 11, 12, 13, 18, 20, 21, 24, 27, 28], "product": [0, 1, 3, 5, 6, 7, 8, 12, 13, 16, 17, 20, 21, 27, 28, 30], "profess": [0, 27], "program": [0, 1, 4, 5, 6, 8, 12, 14, 15, 20, 21, 23, 24, 25, 27, 28], "programm": 21, "progress": [1, 4, 14, 30], "prohibit": 6, "project": [0, 1, 2, 3, 5, 11, 13, 15, 19, 20, 23, 28, 29, 30], "project_root_dir": [0, 6, 7, 9, 27], "promin": 12, "promis": 8, "promot": [25, 27], "prone": [9, 15], "pronounc": [13, 20, 27, 30], "proof": [0, 11, 12, 13, 27, 29], "prop": 30, "propag": [2, 3, 13, 30], "proper": [0, 2, 6, 7], "properli": [1, 6, 8, 10, 13, 18, 22, 30], "properti": [0, 1, 3, 12, 13, 16, 21, 27], "proport": [0, 1, 5, 9, 11, 13, 24, 27, 28], "propos": [1, 4, 6, 10, 22, 27, 30], "propto": [5, 13, 29, 30], "proton": [0, 27], "prove": [3, 13, 29, 30], "provid": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 20, 21, 22, 24, 27, 28, 29, 30], "proxi": [1, 13, 30], "prune": 9, "pseudo": [21, 24, 30], "pseudocod": 22, "pseudoinv": 5, "pseudoinvers": [5, 6, 22], "pseudorandom": [6, 24], "psychologi": [0, 27], "pt": 13, "public": [0, 15, 20, 27], "pull": 15, "punish": [0, 1, 27], "pure": [3, 9, 24], "purest": 9, "puriti": 9, "purpos": [0, 3, 10, 12, 14, 27], "push": 15, "put": 1, "py": 5, "pycod": 27, "pydata": 20, "pydot": 9, "pyhton2": 27, "pylab": [7, 27], "pypi": 20, "pyplot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 24, 27, 28, 29, 30], "pythagora": 5, "python": [1, 2, 3, 5, 6, 8, 11, 12, 13, 14, 18, 22, 24, 28, 30], "python2": [0, 22], "python3": [0, 20, 22, 27], "pytorch": [0, 20, 22, 27], "q": [5, 6, 8, 11, 24], "qp": 8, "qquad": [2, 11, 13, 21, 30], "qr": [5, 6, 21, 28, 29], "quad": [1, 13, 21], "quadrat": [0, 8, 9, 13, 27], "qualit": [4, 9, 22, 24], "qualiti": [0, 9, 20, 27, 28], "quantifi": 1, "quantil": 10, "quantit": [0, 6, 9, 22, 27], "quantiti": [0, 2, 5, 6, 7, 9, 10, 11, 12, 14, 16, 21, 24, 27, 28, 29, 30], "quantum": [4, 12, 26, 27], "quartil": [0, 28, 30], "quench": 5, "queri": 9, "question": [0, 5, 6, 9, 11, 12, 13, 22, 25, 27, 28, 30], "qugan": 4, "quick": [4, 24], "quickli": [1, 3, 9, 11, 13, 29], "quit": [1, 5, 6, 9, 10, 12, 15, 28, 29], "quot": 4, "r": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 20, 21, 22, 24, 28, 29, 30], "r2": [0, 5, 6, 27, 28, 29], "r2_score": [0, 27], "r2score": [0, 27], "r_": 30, "r_0": 30, "r_1": 9, "r_2": 9, "r_j": 9, "r_m": 9, "r_t": 30, "rad": [], "rade": [], "radial": [8, 12], "radioact": 24, "radiu": [0, 1, 28, 30], "rain": 9, "ramp": 1, "ran0": 24, "ran1": 24, "ran2": 24, "ran3": 24, "rand": [0, 4, 5, 6, 9, 10, 13, 15, 19, 21, 27, 28, 29, 30], "randint": [6, 9, 13, 30], "randn": [0, 1, 2, 5, 6, 9, 11, 13, 15, 18, 27, 28, 29, 30], "random": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 17, 18, 19, 20, 21, 27, 28, 29, 30], "random_forest_model": 10, "random_index": [13, 30], "random_indic": [1, 3], "random_st": [7, 8, 9, 10, 11], "randomforestclassifi": 10, "randomli": [1, 6, 9, 13, 14, 18, 29, 30], "rang": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 19, 21, 24, 27, 28, 29, 30], "rangl": [0, 6, 11, 24, 27, 28], "rangle_x": 24, "rank": [5, 28, 29], "rankdir": 4, "raphson": [1, 8, 13], "rapidli": 0, "rare": [1, 13, 30], "raschka": [27, 28], "rasckha": 27, "rashcka": [29, 30], "rate": [1, 2, 3, 4, 8, 9, 10, 12, 13, 18, 29], "rather": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 24, 27, 28, 29], "ratio": [4, 7, 9, 10, 11], "rational": [0, 27], "ravel": [5, 6, 7, 8, 9, 10, 11, 13, 21], "raw": [3, 30], "rbf": [8, 11, 12], "rbf_kernel_svm_clf": 8, "rbf_pca": 11, "rc": 24, "rcond": [0, 27, 28], "rcparam": [1, 3, 7, 8, 9, 10, 24, 27], "re": [2, 4, 13, 15, 29], "reach": [1, 4, 5, 6, 9, 10, 12, 13, 14, 29, 30], "read": [0, 2, 3, 4, 5, 6, 7, 8, 11, 12, 16, 17, 21, 22, 24, 26, 29], "read_csv": [0, 6, 7, 9], "read_fwf": [0, 27], "reader": [0, 6, 21, 24, 27, 28, 30], "readi": [0, 1, 5, 6, 8, 10, 11, 12, 21, 27], "readili": 1, "readm": 15, "readthedoc": 20, "real": [0, 1, 4, 7, 10, 11, 12, 16, 18, 19, 21, 28], "real_loss": 4, "real_output": 4, "realist": [8, 27], "realiti": 24, "realiz": [1, 12], "realli": [0, 1, 27], "rearrang": 13, "reason": [0, 1, 3, 4, 10, 13, 26, 27, 29, 30], "reassign": 1, "recal": [5, 6, 9, 10, 11, 12, 21, 24, 27, 28, 29, 30], "recast": 3, "receiv": [1, 3, 10, 12, 24], "recent": [0, 6, 13, 26, 30], "recept": [3, 12], "receptive_field": 3, "recip": [0, 6, 7, 21, 22, 27, 28], "reciproc": 5, "recogn": [0, 4, 5, 10, 27], "recognit": [0, 1, 3, 12, 26, 27], "recommen": 27, "recommend": [0, 2, 3, 4, 5, 6, 8, 13, 15, 19, 20, 21, 22, 26, 29, 30], "reconsid": 9, "reconstruct": 11, "record": [10, 22, 23, 25, 27], "recreat": 15, "rectangl": [9, 13, 29], "rectangular": [5, 28, 29], "rectifi": [1, 3, 12], "recur": [0, 20, 27], "recurr": [0, 1, 20, 27], "recurs": [9, 20, 21, 27], "red": [0, 3, 4, 6, 8, 9, 30], "redefin": [0, 10, 27, 28, 29], "redefinit": 29, "reduc": [1, 3, 5, 6, 9, 10, 11, 13, 27, 29, 30], "reduct": [0, 10, 11, 20, 24, 27, 28], "reegress": 22, "refer": [0, 1, 2, 3, 5, 6, 11, 12, 13, 14, 21, 26, 27, 28, 29, 30], "referenc": 2, "refin": 12, "refit": 6, "reflect": [0, 1, 4, 5, 22, 24, 27], "refresh": [20, 27], "refreshprogrammingskil": 27, "reg": [10, 11], "regard": [1, 9, 13], "regardless": [12, 16], "region": [3, 4, 6, 9, 12, 22], "regist": [6, 24], "reglasso": [5, 29], "regr_1": [0, 9], "regr_2": [0, 9], "regr_3": [0, 9], "regress": [1, 8, 11, 12, 16, 20, 21], "regressor": [0, 7, 10], "regret": [], "regridg": [0, 5, 6, 28, 29, 30], "regular": [0, 3, 4, 5, 6, 7, 9, 13, 17, 18, 25, 27, 28, 29, 30], "regularli": 15, "reilli": [0, 26, 27], "reinforc": [0, 8, 20, 27], "reiter": 1, "reject": 7, "rel": [0, 4, 6, 7, 9, 12, 13, 24, 27, 28, 30], "relat": [0, 1, 3, 4, 5, 11, 13, 14, 19, 21, 24, 27, 28, 29], "relationship": [0, 4, 9, 18, 27], "relativeerror": [0, 27, 28], "releas": [1, 20, 27], "relev": [0, 1, 5, 7, 11, 20, 22, 24, 27, 29], "reli": [0, 6, 8], "reliabilti": 22, "reliabl": [7, 24], "relu": [3, 4, 27], "remain": [1, 2, 4, 6, 12, 21, 24, 28, 30], "remaind": 24, "reman": 2, "remark": 1, "rememb": [0, 8, 13, 21, 22, 27], "remind": [0, 5, 11, 13, 21, 24], "remot": 15, "remov": [4, 5, 6, 18, 28, 29, 30], "renam": 15, "render": [0, 27, 28], "reorder": [5, 7, 28, 29], "reorgan": [0, 27], "repeat": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 14, 21, 22, 24, 27, 28, 29, 30], "repeated": 27, "repeatedli": [0, 6, 10, 13], "repet": 3, "repetit": [6, 27, 28], "rephras": [13, 29], "replac": [0, 1, 3, 4, 5, 6, 10, 12, 14, 20, 22, 27, 28, 29], "replica": 6, "repo": [15, 22], "report": [27, 30], "repositori": [4, 22, 27], "repres": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 22, 24, 27, 28, 29, 30], "represent": [0, 1, 3, 6, 24, 27], "representd": 3, "reproduc": [0, 5, 6, 9, 12, 15, 16, 18, 20, 24, 27, 28], "repuls": [0, 27], "request": [0, 13, 30], "requir": [0, 1, 3, 4, 5, 6, 8, 9, 11, 12, 13, 15, 17, 18, 21, 27, 28, 29, 30], "res1": 2, "res2": 2, "res3": 2, "res_analyt": 2, "res_analytical1": 2, "res_analytical2": 2, "res_analytical3": 2, "resaml": 6, "resampl": [0, 7, 10, 20, 27, 28], "rescal": [0, 11, 12, 30], "rescu": 5, "reseach": 6, "research": [0, 4, 13, 20, 26, 27], "resembl": [6, 24], "reserv": [1, 5, 6, 24], "reshap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 21, 27, 28], "residenti": [], "residu": [0, 5, 13, 27], "resiz": [5, 28, 29], "resourc": 27, "respect": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 17, 18, 22, 24, 27, 28, 29, 30], "respond": 12, "respons": [0, 7, 9, 12, 27, 28], "rest": [0, 5, 18, 28, 29, 30], "restat": [0, 12, 27], "restor": 4, "restored_discrimin": 4, "restored_gener": 4, "restrict": [0, 3, 9, 12, 27], "result": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 27, 30], "retail": [], "retain": [5, 6, 28, 29, 30], "return": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 21, 24, 27, 28, 29, 30], "return_data": 14, "return_sequ": 4, "return_x_i": 9, "reus": [1, 3, 6, 19, 22], "reveal": [0, 12, 27], "revers": [1, 21], "review": [20, 21], "revisit": 14, "revolut": 27, "reward": [0, 4, 27], "rewrit": [0, 3, 5, 6, 7, 8, 10, 11, 12, 13, 16, 19, 21, 22, 24, 29, 30], "rewritten": [2, 6, 8, 10, 24], "rewrot": 13, "rf": 10, "rgb": 3, "rgoj5yh7evk": 20, "rh": 6, "rho": [0, 10, 13, 30], "rho_1": 10, "rho_2": 10, "rho_m": 10, "rich": [0, 27], "ride": 9, "rideclass": 9, "ridedata": 9, "ridg": [7, 11, 13, 20, 27], "ridge_paramet": 17, "ridge_sk": 6, "ridgebeta": 29, "ridgetheta": 5, "right": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "right_sid": 2, "rightarrow": [0, 1, 5, 6, 8, 11, 12, 13, 24, 27, 28, 29, 30], "rigor": [0, 27, 28, 29], "ring": 6, "rise": [0, 27], "risk": [0, 13, 27, 29, 30], "rival": 4, "river": [], "rlm": 27, "rm": [24, 30], "rmse": [], "rmsporp": [13, 30], "rmsprop": [1, 3, 4, 13, 22], "rnd_clf": 10, "rng": 24, "rnn": [4, 12], "rnn1": 4, "rnn2": 4, "rnn_2layer": 4, "rnn_input": 4, "rnn_output": 4, "rnn_train": 4, "rntrick1": 24, "rntrick2": 24, "rntrick3": 24, "rntrick4": 24, "ro": [0, 13, 27, 29, 30], "robert": [19, 22, 26], "robust": [0, 27, 30], "robustscal": [0, 28, 30], "roc": [7, 10], "role": [0, 2, 5, 6, 8, 18, 20, 22, 27, 28, 29, 30], "roll": 6, "room": [0, 25, 27], "root": [0, 5, 9, 13, 15, 24, 28, 29, 30], "rot": 27, "rotat": [1, 8, 9, 10], "rotation_matrix": 9, "roughli": [1, 3, 18], "round": [7, 9, 13], "routin": [13, 21, 27, 29], "row": [0, 1, 2, 5, 6, 9, 11, 16, 21, 27, 28, 29], "rr": [5, 28, 29], "rrr": [5, 28, 29], "rudg": [], "rug": [13, 29, 30], "rule": [0, 1, 5, 6, 13, 22, 27, 28, 29], "run": [0, 1, 2, 4, 5, 6, 8, 9, 11, 13, 15, 20, 22, 27, 28, 29, 30], "runtim": [1, 6, 14, 15], "rust": [0, 20, 21, 27], "rvert": 1, "rvert_2": 1, "s_": [3, 6], "s_1": 6, "s_i": [6, 7], "s_j": 6, "s_k": 6, "s_phenomenon": 22, "saddl": [13, 29, 30], "safeguard": [18, 30], "sai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 21, 22, 24, 27, 28, 29], "said": [6, 9, 13, 29], "sake": [0, 5, 7, 11, 27, 28, 29], "sale": [0, 27], "sam": 27, "same": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 18, 21, 22, 24, 27, 28, 29], "samm": 10, "sampl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 14, 18, 19, 20, 21, 22, 24, 27, 28, 30], "sample_vari": 14, "sampleexptvari": 24, "samwis": 27, "sastri": 11, "satisfactori": [0, 27], "satisfi": [1, 2, 3, 6, 8, 13, 21, 24, 29], "satur": [1, 6], "save": [0, 4, 6, 7, 9, 13, 27, 30], "save_fig": [0, 6, 7, 9, 10, 27], "savefig": [0, 4, 6, 7, 9, 24, 27], "savetxt": 4, "saw": [5, 28], "scalabl": 10, "scalar": [2, 5, 6, 10, 28], "scale": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20, 21, 22, 25, 27, 29], "scale_mean": 4, "scale_std": 4, "scaler": [0, 7, 8, 9, 10, 11, 17, 22, 28], "scan": [5, 7], "scari": 5, "scatter": [0, 1, 6, 7, 8, 9, 14, 15, 17, 27, 28, 30], "scenario": [6, 13, 29, 30], "schedul": [13, 30], "scheme": [1, 13, 29, 30], "schrage": 24, "sch\u00f8yen": [6, 28, 30], "scienc": [0, 1, 10, 12, 13, 20, 23, 24, 25, 26, 29], "scientif": [0, 20, 22, 27], "scientist": [0, 27], "scikit": [3, 5, 6, 8, 9, 10, 13, 15, 16, 20, 21, 22, 26], "scikit_learn": 0, "scikitlearn": 27, "scikitplot": [7, 10], "scipi": [0, 3, 5, 6, 13, 20, 21, 22, 27, 28, 29], "scl": 6, "scm": 15, "score": [0, 1, 3, 6, 7, 9, 10, 11, 15, 16, 22, 25, 27, 28, 30], "scores_kfold": 6, "scratch": [1, 13, 16], "sdg": [13, 30], "sdv4f4s2sb8": [29, 30], "seaborn": [0, 1, 3, 6, 7, 27], "seamless": [0, 20, 22, 27], "search": [0, 1, 3, 5, 9, 13, 15, 27, 29, 30], "sebastian": 27, "sebastianraschka": 27, "sec": 6, "second": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 14, 15, 16, 20, 21, 24, 25, 27, 28, 29], "second_mo": 30, "second_term": 30, "secondeigvector": 11, "secondli": 12, "section": [4, 11, 16, 21, 22, 24, 28, 30], "sector": 0, "see": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "seed": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 18, 24, 27, 28, 29, 30], "seed_imag": 4, "seek": [1, 2, 8], "seem": [1, 3, 4, 30], "seemingli": [0, 27], "seen": [0, 1, 3, 5, 10, 12, 24], "segment": [13, 29], "seismic": 6, "seldomli": [0, 27], "select": [1, 5, 6, 8, 9, 10, 11, 15, 22, 23, 24, 25, 26, 27, 28, 29], "selevet": 15, "self": [1, 5, 28], "sell": 4, "semest": [7, 23], "semi": [8, 13, 29, 30], "semilogx": 6, "send": [5, 12, 13, 25, 27], "senior": [23, 25], "sens": [0, 4, 6, 8, 27], "sensibl": 3, "sensit": [0, 5, 6, 9, 13, 27, 28, 30], "sent": 2, "sentenc": [4, 12], "separ": [0, 1, 2, 4, 6, 8, 9, 12, 14, 18, 20, 22, 24, 27, 30], "septemb": [18, 22, 27], "sequenc": [3, 4, 7, 9, 10, 12, 13, 20, 21, 24, 27, 29], "sequenti": [1, 3, 4, 10, 12, 24], "seri": [0, 1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 21, 27, 28, 29], "serif": [7, 24, 27], "serv": [0, 1, 2, 3, 5, 7, 13, 26, 27, 28, 29, 30], "servic": 22, "session": [1, 15, 22, 23, 25, 27], "set": [1, 4, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 18, 20, 21, 22, 24, 25, 30], "set_major_formatt": 6, "set_major_loc": 6, "set_tick": [1, 8], "set_ticklabel": 1, "set_titl": [0, 1, 2, 3, 7, 12, 14, 27], "set_xlabel": [0, 1, 2, 3, 7, 12, 27], "set_xlim": [7, 12], "set_xticklabel": 1, "set_ylabel": [0, 1, 2, 3, 7, 27], "set_ylim": [7, 12], "set_ytick": 7, "set_yticklabel": [1, 6], "set_zlim": 6, "seth": 4, "setminu": 6, "setosa": [8, 9], "setosa_or_versicolor": 8, "setp": 6, "setup": [1, 4, 6, 8, 20, 27, 28, 29], "sever": [0, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 20, 21, 22, 24, 27, 28, 29, 30], "sgd": [1, 3, 29], "sgd_clf": 8, "sgdclassifi": 8, "sgdreg": 13, "sgdregressor": 13, "sgn": [5, 28, 29], "shallow": [13, 30], "shape": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 21, 27, 28, 29, 30], "share": [1, 3, 15, 27], "shareabl": 15, "she": 7, "shift": [1, 6, 12, 15, 18, 24, 28, 30], "ship": 3, "shire": 27, "short": [4, 5, 22], "shortcom": [13, 29, 30], "shorten": 4, "shorter": 24, "shorthand": 27, "shortli": [21, 27], "should": [0, 2, 3, 5, 6, 8, 9, 11, 12, 15, 18, 21, 22, 24, 27, 28, 30], "show": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "show_shap": 4, "shown": [0, 4, 5, 8, 12, 13, 21, 28, 29, 30], "shrink": [3, 5, 6, 8, 11, 28, 29], "shrinkag": [5, 6, 28, 29], "shrunk": 11, "shuffl": [0, 1, 4, 6, 13, 28, 30], "side": [0, 2, 5, 8, 12, 13, 21, 22, 27, 29], "sigh": [20, 27], "sigma": [0, 1, 5, 6, 7, 10, 11, 12, 13, 19, 21, 22, 24, 27, 28, 29, 30], "sigma0": 24, "sigma1": 24, "sigma2": 24, "sigma_": [5, 21, 27, 28, 29], "sigma_0": [5, 28, 29], "sigma_1": [5, 28, 29], "sigma_2": [5, 28, 29], "sigma_fn": [7, 12], "sigma_i": [0, 5, 27, 28, 29], "sigma_j": [5, 28, 29], "sigma_m": [6, 24], "sigma_n": [11, 24], "sigma_t": 13, "sigma_x": 24, "sigmoid": [1, 2, 4, 7, 8, 10, 12], "sigmundson": [6, 28, 30], "sign": [1, 2, 7, 8, 10, 24, 25], "signal": [1, 3, 10, 12, 30], "signifi": 4, "signific": [1, 30], "significantli": [1, 13, 18, 24, 29, 30], "sim": [4, 5, 6, 13, 19, 24], "similar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 18, 20, 21, 22, 27, 29], "similarli": [0, 1, 3, 5, 8, 10, 13, 24, 27, 28, 29, 30], "simpl": [1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 14, 16, 17, 20, 21, 24], "simplepredict": 10, "simpler": [0, 1, 5, 6, 7, 13, 16, 20, 22, 27, 29, 30], "simplernn": 4, "simplest": [0, 1, 3, 4, 9, 10, 12, 14, 22, 27], "simpletre": 10, "simpli": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 20, 21, 22, 24, 27, 28, 29, 30], "simplic": [2, 5, 6, 7, 8, 9, 10, 11, 12, 14, 28, 29, 30], "simplicti": [5, 28, 29], "simplifi": [0, 6, 9, 18, 20, 22, 27, 28, 30], "simplist": [3, 6, 24], "simul": [6, 18], "simultan": 6, "sin": [0, 1, 2, 3, 4, 9, 12, 13, 21, 27], "sinc": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 16, 18, 21, 22, 24, 26, 27, 28, 29, 30], "sine": [3, 12], "singl": [0, 1, 2, 3, 5, 6, 7, 8, 9, 12, 13, 18, 19, 21, 24, 27, 28, 29, 30], "singular": [0, 6, 13, 21, 27], "sinusoid": 3, "site": [0, 22, 23, 28], "situat": [0, 4, 5, 7, 13, 24, 27, 28, 29, 30], "six": [3, 24], "size": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 18, 21, 22, 24, 27], "sizesp": 30, "sketch": 10, "ski": 9, "skill": 0, "skip": 11, "skl": [0, 6, 27, 28, 30], "sklearn": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 19, 27, 28, 29, 30], "skplt": [7, 10], "sl": [6, 28, 30], "slack": 8, "slice": [2, 21, 27], "slide": [0, 3, 16, 22, 24, 27, 28, 29], "slight": [6, 13], "slightli": [1, 2, 3, 5, 6, 7, 10, 24, 28, 29], "slope": [8, 11, 12], "slow": [0, 2, 8, 13, 18, 28, 29, 30], "slower": [5, 21, 27, 28, 29, 30], "slowest": 21, "slowli": [12, 30], "slp": 1, "small": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 18, 20, 21, 24, 27, 28, 29, 30], "smaller": [0, 1, 2, 5, 6, 8, 9, 11, 13, 24, 27, 28, 29, 30], "smallest": [0, 4, 14, 27], "smallest_row_index": 14, "smooth": [0, 3, 6, 13, 22, 27, 29, 30], "smoother": 30, "sn": [0, 1, 3, 6, 7, 27], "sne": 11, "so": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "soar": 6, "social": 0, "soft": [1, 7, 10, 12], "soften": 8, "softmax": [3, 7], "softwar": [0, 8, 20, 21], "sol": 8, "sole": [0, 6, 27], "solid": [0, 7], "solut": [0, 1, 2, 3, 5, 6, 8, 10, 11, 13, 18, 21, 22, 24, 27, 28, 29, 30], "solution_ev": 30, "soluton": 2, "solv": [0, 1, 3, 5, 6, 8, 10, 11, 12, 13, 16, 21, 22, 27, 28], "solve_expdec": 2, "solve_ode_deep_neural_network": 2, "solve_ode_neural_network": 2, "solve_pde_deep_neural_network": 2, "solveod": 2, "solveode_popul": 2, "solver": [2, 7, 8, 9, 10, 21, 27], "some": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 22, 24, 27, 30], "some_model": [6, 28, 30], "somehow": 4, "someon": 16, "someth": [0, 1, 3, 4, 7, 9, 11, 15, 19, 22, 24, 27, 28], "sometim": [0, 1, 11, 12, 13, 14, 28, 30], "soon": [21, 25, 28], "sophist": [0, 27], "sopt": 13, "sort": [5, 6, 9, 11, 24], "sound": [3, 5], "sourc": [0, 1, 3, 6, 20, 21, 22, 24, 27], "space": [0, 1, 4, 5, 8, 9, 11, 12, 13, 14, 24, 28, 29, 30], "span": [0, 3, 5, 9, 11, 21, 27, 28, 29], "spare": 1, "spars": [3, 6, 18, 21, 27, 30], "sparse_mtx": [21, 27], "sparsecategoricalcrossentropi": 3, "sparsiti": [10, 18], "spatial": [1, 2, 3, 12], "speak": 24, "special": [6, 7, 10, 12, 13, 21, 24, 27, 28, 29, 30], "specif": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 15, 16, 20, 21, 22, 24, 26, 27, 28, 29], "specifi": [0, 3, 5, 6, 7, 9, 11, 13, 14, 24, 27, 29, 30], "specifici": [0, 10, 27], "spectacular": 3, "spectral": 1, "speech": [0, 1, 3, 4, 12], "speed": [1, 2, 4, 13, 30], "spend": [16, 24], "spent": 22, "sphere": [0, 28, 30], "spin": 6, "spite": 0, "spline": 8, "split": [1, 3, 4, 5, 6, 8, 9, 10, 11, 14, 16, 17, 22, 24, 27, 29, 30], "splite": 0, "splitter": [1, 10], "spontan": 24, "spot": 3, "spread": [0, 11, 24, 27, 28], "springer": [19, 22, 26, 27], "spuriou": [13, 30], "sqquar": 29, "sqrsignal": 3, "sqrt": [3, 4, 5, 6, 8, 10, 11, 13, 24, 28, 29, 30], "squar": [1, 2, 3, 4, 7, 8, 9, 11, 13, 14, 15, 17, 18, 20, 21, 24], "squarederror": 10, "squaredeuclidean": 14, "squash": 12, "srtm": 6, "srtm_data_norway_1": 6, "stabil": [5, 22, 30], "stabl": [0, 4, 5, 6, 9, 16, 20, 22, 27, 28, 29], "stack": [3, 4], "stage": [5, 13, 15, 22, 30], "stai": [0, 2, 4, 5, 11, 27, 28, 30], "stand": [0, 5, 9, 12, 27, 28, 29], "standard": [0, 1, 4, 5, 6, 7, 8, 10, 12, 17, 18, 21, 22, 24, 27, 29, 30], "standardscal": [0, 6, 7, 8, 9, 10, 11, 17, 28, 30], "stanford": [13, 29], "start": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 21, 24, 25, 27, 28, 29, 30], "start_tim": 14, "stat": 6, "state": [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 20, 24, 27, 28, 29], "statement": [0, 7, 21, 27], "stationari": [29, 30], "statist": [0, 1, 3, 4, 7, 9, 10, 11, 12, 13, 14, 19, 21, 22, 26, 28, 29, 30], "statu": [0, 7, 15, 27], "stavang": 6, "std": [0, 4, 6, 18, 27, 28, 30], "steep": [13, 29, 30], "steepest": 30, "step": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 21, 22, 27, 29], "step_fn": [7, 12], "step_length": [13, 30], "step_siz": 30, "steps_list": 9, "stereo": 3, "still": [0, 2, 3, 5, 6, 11, 13, 24, 28, 29, 30], "stimuli": 12, "stk": [26, 27], "stk2100": [26, 27], "stk3155": [15, 22, 23, 25], "stk4021": [26, 27], "stk4051": [26, 27], "stk4155": [23, 25], "stk5000": 26, "stochast": [0, 1, 5, 6, 8, 11, 12, 29], "stock": 4, "stoke": 12, "stone": [0, 7], "stop": [1, 4, 9, 13, 14, 18, 29], "storag": [5, 28, 29], "store": [0, 1, 2, 3, 6, 11, 13, 24, 27, 30], "storehaug": [25, 27], "str": [1, 3, 4], "straight": [0, 6, 8, 13, 27, 29], "straightforward": [0, 2, 3, 5, 6, 8, 9, 10, 13, 21, 27, 28, 29], "strategi": [0, 1, 9, 27], "stratifi": 6, "strength": [0, 5, 14, 28, 29], "stretch": 11, "strict": [8, 13, 29], "strictli": [8, 13, 29], "stride": [4, 21], "strike": 6, "string": 1, "stroke": 7, "strong": [3, 6, 9, 10, 12, 21, 24], "strongli": [0, 8, 15, 20, 21], "stronli": [], "structur": [0, 1, 2, 3, 6, 9, 10, 12, 20, 27], "stuck": [1, 13, 29, 30], "student": [0, 15, 22, 23, 25, 26, 27], "studi": [0, 3, 4, 5, 6, 7, 8, 11, 12, 13, 20, 22, 26, 27, 28, 29, 30], "studier": 26, "style": [7, 9, 21, 27], "st\u00f8land": 25, "sub": [9, 12, 30], "subdivid": [0, 21, 27], "subfield": 0, "subgradi": 30, "subject": [6, 8, 24], "submit": 27, "subplot": [0, 1, 3, 4, 6, 7, 8, 9, 10, 14, 27], "subplots_adjust": [8, 24], "subprogram": [21, 27], "subract": [0, 28], "subroutin": [0, 27], "subscript": 1, "subsequ": [1, 4, 5, 6, 12, 21, 24, 28, 29], "subset": [1, 6, 9, 12, 13, 20, 27, 29, 30], "subspac": [0, 8, 11, 28], "substanti": [9, 10], "substep": 11, "substitut": [3, 6, 12, 16, 21], "subsubset": 9, "subtask": 6, "subtl": 1, "subtract": [0, 4, 5, 6, 11, 13, 18, 21, 22, 24, 28, 30], "subtre": 9, "succeed": [0, 4, 27], "success": [3, 7, 9, 13, 24], "successfulli": [4, 9], "sudo": [0, 20, 22, 27], "suffer": [0, 1, 2, 5, 10, 27, 28, 29], "suffici": [1, 6, 8, 11, 13, 29], "suggest": [1, 13, 22, 26, 29, 30], "suit": [8, 12], "suitabl": [0, 15, 19, 24, 28], "sum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 19, 21, 24, 27, 28, 29, 30], "sum_": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 19, 21, 22, 24, 27, 28, 29, 30], "sum_i": [0, 2, 5, 6, 8, 13, 19, 22, 28, 29, 30], "sum_j": [6, 18, 30], "sum_ja_": 0, "sum_k": [6, 8, 12, 21], "sum_logist": 13, "sum_m": 3, "sum_n": 3, "sum_nx_": 3, "summar": [5, 6, 9], "summari": [1, 3, 4, 10, 23, 29], "summat": [0, 3, 16, 28, 29], "sunni": 9, "super": [5, 28, 29], "superfici": 3, "superscript": [1, 12], "supervis": [0, 5, 6, 7, 9, 12, 20, 27, 28, 29], "supplement": [7, 22], "support": [0, 1, 9, 10, 11, 13, 20, 27, 28], "suppos": [0, 5, 6, 7, 8, 10, 11, 12, 13, 21, 27, 28, 29, 30], "suppress": [5, 13, 29], "sure": [0, 1, 4, 6, 16, 22], "surf": 6, "surfac": [0, 6, 27], "surpass": 6, "surpris": [0, 27], "surround": [3, 20], "survei": [0, 5, 6, 27, 28], "svc": [8, 9, 10], "svd": [0, 6, 11, 27], "svdinv": 5, "svm": [8, 9, 10, 11], "svm_clf": [8, 10], "swath": [5, 28, 29], "switch": 0, "sy": [13, 29, 30], "symbol": [1, 5, 11, 13, 20, 24, 27, 28, 29], "symmeteri": 1, "symmetr": [0, 5, 8, 11, 12, 13, 21, 27, 28], "symmetri": 6, "sympi": [0, 20, 22, 27], "synonim": 24, "syntax": 13, "system": [0, 1, 3, 4, 6, 7, 9, 10, 12, 13, 15, 20, 21, 22, 27, 29], "systemat": [4, 6], "t": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 27, 29, 30], "t0": [3, 6, 13, 30], "t1": [2, 13, 30], "t2": 2, "t3": 2, "t_": 2, "t_0": [2, 9, 13, 30], "t_1": [13, 30], "t_b": 10, "t_i": [1, 2, 5, 12, 28, 29], "t_j": 12, "t_k": 9, "tabl": [9, 22, 24, 25, 27], "tabul": [0, 27], "tabular": 27, "tackl": 4, "tag": [2, 3, 4, 5, 6, 7, 12, 13, 14, 21, 24, 28, 29], "taht": [0, 27], "tail": 24, "tailor": [2, 8, 11, 27], "taiwan": [0, 27], "take": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 20, 21, 24, 27, 28, 29, 30], "taken": [0, 1, 3, 6, 10, 13, 21], "tan": 3, "tangent": [1, 4, 12, 13, 29], "tanh": [1, 4, 7, 8, 12], "target": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 18, 19, 27, 28, 29, 30], "target_nam": 9, "task": [0, 1, 3, 6, 9, 11, 12, 14, 22, 27], "tau": [3, 5, 24], "taught": 27, "tax": [], "taylor": [2, 13, 29], "taylornr": [13, 29], "tc": 8, "teach": [15, 23, 27], "team": 1, "teaser": 0, "technic": [0, 5, 6, 13, 22, 29, 30], "techniqu": [0, 1, 8, 10, 13, 20, 24, 26, 27, 28, 30], "technologi": [0, 1], "tell": [0, 4, 6, 10, 11, 13, 16, 24, 30], "temp": 1, "temp1": 1, "temp2": 1, "temperatur": [0, 9, 27], "templat": 18, "temporarili": 1, "ten": [3, 27], "tend": [3, 5, 6, 8, 9, 10, 12, 13, 14, 28, 30], "tendenc": [0, 27], "tension": 6, "tensor": 3, "tensorflow": [0, 2, 4, 8, 14, 20, 21, 22, 26, 27, 28], "term": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 22, 24, 27, 28, 29, 30], "term1": [5, 6, 11], "term2": [5, 6, 11], "term3": [5, 6, 11], "term4": [5, 6, 11], "termin": [0, 4, 5, 9, 10, 13, 15, 28, 29, 30], "terminarl": 15, "terrain": 6, "terrain1": 6, "test": [3, 4, 5, 6, 7, 8, 9, 10, 13, 16, 21, 22, 24, 27, 29, 30], "test_acc": 3, "test_accuraci": [1, 3], "test_error": 6, "test_imag": [3, 4], "test_ind": 6, "test_input": 4, "test_label": [3, 4], "test_loss": 3, "test_pr": 1, "test_predict": 1, "test_rnn": 4, "test_scor": [7, 10], "test_siz": [0, 1, 3, 5, 6, 10, 15, 17, 28, 29, 30], "test_split": 9, "testerror": [0, 6, 28], "testi": 4, "testpredict": 4, "testx": 4, "text": [0, 1, 2, 4, 5, 8, 9, 11, 13, 15, 18, 21, 24, 26, 28, 29, 30], "textbf": [], "textbook": [16, 22, 28, 29], "textual": 9, "textur": 1, "tf": [1, 3, 4, 13, 14, 29], "th": [0, 1, 2, 5, 6, 7, 9, 12, 13, 14, 21, 22, 24, 27, 28, 30], "than": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 17, 20, 24, 27, 28, 30], "thank": [4, 6, 28, 30], "theano": [1, 20, 27], "thei": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 18, 21, 22, 24, 27, 28, 29, 30], "them": [0, 1, 3, 4, 6, 8, 9, 10, 11, 12, 13, 18, 19, 21, 22, 27, 28], "theme": [0, 15, 27], "themselv": [0, 22, 24, 27], "thenc": 6, "theorem": [2, 6, 7, 28, 29], "theoret": [0, 4, 10], "theori": [0, 1, 3, 8, 9, 12, 13, 19, 20, 22, 26, 27], "thereaft": [0, 5, 6, 11, 12, 21, 22, 27], "therebi": [0, 5, 7, 11, 22, 27, 28, 29], "therefor": [0, 1, 2, 3, 4, 6, 7, 8, 11, 13, 19, 24, 27, 28, 29, 30], "therein": 11, "thereof": [0, 6, 13, 27, 30], "theta": [0, 1, 4, 5, 6, 7, 13, 16, 22, 24, 27, 28, 29, 30], "theta1": 30, "theta2": 30, "theta_": [0, 1, 6, 7, 13, 27, 28, 29, 30], "theta_0": [0, 5, 6, 7, 16, 27, 28, 29, 30], "theta_0x_": [0, 27, 28], "theta_1": [0, 5, 6, 7, 27, 28, 29, 30], "theta_1x_": [0, 27, 28], "theta_1x_0": [0, 27], "theta_1x_1": [0, 7, 27], "theta_1x_2": [0, 27], "theta_1x_i": [7, 28, 29, 30], "theta_2": [0, 27, 28], "theta_2x_": [0, 27, 28], "theta_2x_0": [0, 27], "theta_2x_1": [0, 27], "theta_2x_2": [0, 7, 27], "theta_2x_i": 28, "theta_3x_i": 28, "theta_4x_i": 28, "theta_closed_form": 18, "theta_closed_formol": 18, "theta_closed_formridg": 18, "theta_gdol": 18, "theta_gdridg": 18, "theta_i": [0, 1, 5, 27, 28, 29], "theta_j": [0, 5, 6, 18, 27, 28, 30], "theta_k": [29, 30], "theta_linreg": [13, 29, 30], "theta_ol": 18, "theta_p": 7, "theta_px_p": 7, "theta_ridg": 18, "theta_t": [13, 30], "theta_tru": 18, "thetavalu": 5, "thi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 28, 29, 30], "thing": [0, 1, 2, 4, 5, 7, 9, 15, 16, 18, 24, 27], "think": [0, 1, 3, 4, 6, 9, 12, 13, 14, 24, 27, 28, 29, 30], "third": [0, 3, 6, 13, 25, 27, 29, 30], "thirti": 7, "thorughout": 27, "those": [0, 3, 5, 6, 8, 9, 10, 11, 21, 22, 27, 28, 29, 30], "though": [1, 2, 3, 4, 13, 16, 17, 21, 24, 30], "thought": [6, 14, 22, 24], "thousand": [0, 1, 22, 28, 30], "three": [0, 1, 3, 5, 6, 8, 9, 12, 21, 22, 23, 24, 25, 27, 28, 29], "threshold": [1, 3, 9, 10, 11, 12, 13, 30], "through": [0, 1, 2, 3, 4, 5, 6, 8, 11, 12, 13, 14, 15, 20, 21, 22, 24, 27, 28, 29, 30], "throughout": [0, 4, 5, 14, 15, 20, 21, 24, 27], "throw": [3, 6, 24], "thu": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 25, 27, 28, 29, 30], "thumb": [0, 6, 22, 28], "thursdai": [], "tibshirani": [6, 19, 22, 26, 27], "tick_param": 6, "ticker": [6, 13, 24, 29, 30], "tif": 6, "tight_layout": [1, 7], "tightli": 11, "tild": [0, 5, 6, 7, 11, 19, 22, 24, 27, 28, 29, 30], "till": [0, 4, 7, 8, 9, 10, 12, 21, 27, 28], "time": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 27, 28, 29], "timeit": 4, "timer": 4, "tini": 1, "tip": 3, "titl": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 15, 24, 27, 29, 30], "tmp": 13, "tn": [2, 3, 7], "to_categor": [1, 3, 4], "to_categorical_numpi": 1, "to_numer": [0, 6, 27], "todai": 3, "togeth": [0, 3, 6, 8, 11, 13, 20, 27], "toi": 14, "told": 13, "toler": [2, 14], "tolist": 4, "tomographi": 12, "too": [0, 2, 4, 5, 6, 9, 11, 13, 17, 18, 24, 26, 28, 29, 30], "took": [8, 27], "tool": [0, 1, 3, 6, 13, 15, 20, 28], "toolbox": 8, "top": [0, 3, 5, 6, 9, 10, 19, 20, 27], "topic": [0, 5, 6, 7, 8, 20, 22, 28, 29], "topolog": [3, 12], "topologi": [1, 12], "torkjellsdatt": [25, 27], "toss": [10, 24], "total": [0, 1, 2, 3, 4, 6, 7, 8, 10, 11, 12, 13, 14, 21, 24, 25, 27, 28, 29, 30], "total_loss": 4, "totalclustervari": 14, "totalscatt": 14, "toward": [1, 2, 7, 12, 13, 15, 29], "towardsdatasci": 30, "town": [], "tp": [4, 7], "tpng": 9, "tpu": [13, 20, 27], "tqdm": 6, "tr": [], "track": [3, 13, 14, 15, 21, 28, 29, 30], "tract": [], "tractabl": [0, 27, 28], "trade": [5, 9], "tradeoff": [0, 5, 19, 22, 27, 28, 29], "tradit": [0, 1, 4, 6, 27], "train": [2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 16, 17, 22, 29, 30], "train_accuraci": [0, 1, 3, 27], "train_dataset": 4, "train_end": [0, 1, 28], "train_error": 6, "train_imag": [3, 4], "train_ind": 6, "train_label": [3, 4], "train_pr": 1, "train_siz": [0, 1, 3, 28], "train_step": 4, "train_test_split": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "train_test_split_numpi": [0, 1, 28], "trainable_vari": 4, "trained_model": [6, 28, 30], "trainerror": [0, 28], "traini": 4, "training_checkpoint": 4, "training_dataset": 4, "training_gradi": [13, 30], "trainingerror": 6, "trainpredict": 4, "trainscor": 4, "trainx": 4, "trait": [0, 27], "trajectori": 4, "transfer": [9, 27], "transform": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 20, 21, 27, 28, 29, 30], "transit": [6, 12], "translat": [1, 4, 6, 10, 27, 28, 30], "transpos": [1, 5, 11, 21, 28, 29], "travers": [0, 5], "treat": [0, 1, 3, 6, 12, 13, 18, 24, 27, 28, 29, 30], "tree": [0, 1, 20, 27], "tree_clf": [9, 10], "tree_clf_": 9, "tree_clf_sr": 9, "tree_reg": 9, "tree_reg1": 9, "tree_reg2": 9, "trend": 24, "treue": 7, "trevor": [19, 22, 26], "tri": [2, 3, 4, 9, 13, 16], "triain": 0, "trial": [0, 2, 4, 6, 13, 24, 27, 29, 30], "triangl": [13, 29], "triangular": 21, "trick": [3, 4, 8, 11, 13, 24, 30], "trickier": 24, "tridiagon": 21, "trillion": 20, "trivial": [0, 1, 5, 11, 24, 27, 29], "troubl": [0, 8, 12, 15, 28, 30], "truck": 3, "true": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "true_beta": 28, "true_fun": 6, "true_theta": [6, 30], "truli": 27, "try": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 18, 20, 21, 22, 24, 27, 28, 29, 30], "tucker": 8, "tuesdai": [25, 27], "tumor": [7, 9], "tumour": 7, "tunabl": 1, "tune": [4, 9, 13, 21, 27, 30], "turn": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 24, 27, 28, 29, 30], "tutori": [1, 4], "tv": 2, "tveito": 2, "tweak": [1, 4, 10, 24], "twice": [13, 29], "twist": 11, "two": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 17, 21, 22, 23, 24, 26, 27, 28, 29, 30], "tx": [13, 29, 30], "tx_1": [13, 29], "txt": [4, 15], "ty": [13, 29], "type": [0, 1, 3, 6, 8, 10, 13, 21, 24, 28, 29, 30], "typic": [0, 1, 2, 3, 4, 5, 7, 9, 10, 12, 13, 15, 16, 24, 27, 28, 29, 30], "typo": 22, "u": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 21, 22, 24, 26, 27, 28, 29, 30], "u_": 21, "u_i": 12, "u_m": 10, "ua": [0, 27], "ubuntu": [0, 20, 22, 27], "uci": 22, "uio": [15, 22, 25, 26], "un": 14, "unabl": 15, "unari": [21, 27], "unbalanc": [6, 9], "unbias": [0, 5, 6, 27], "uncent": [6, 28, 30], "uncertainti": [0, 5, 27], "uncertitud": 24, "unchang": [1, 3], "uncorrel": [10, 24], "undefin": [5, 28, 29], "under": [0, 1, 5, 6, 10, 13, 20, 22, 27, 28, 29], "underdetermin": [0, 27], "underfit": [1, 6], "underflowproblem": 5, "undergo": 5, "undergradu": [23, 25], "underli": [0, 1, 9, 13, 18, 24, 27, 30], "underset": [4, 14], "understand": [0, 1, 3, 5, 6, 10, 13, 14, 15, 20, 27, 28, 29, 30], "understood": [8, 13], "undesir": 8, "undetermin": [5, 8], "undo": 4, "unexpect": 6, "unexpected": 24, "unexplain": 18, "unfair": [6, 28], "unfortun": [1, 8, 9, 10], "unicode_liter": [8, 9], "uniform": [0, 1, 5, 6, 11, 13, 22, 24, 27, 29, 30], "uniformli": [13, 24, 29, 30], "unifrompdf": 24, "unimport": [13, 29], "union": [5, 6], "uniqu": [0, 2, 6, 13, 14, 21, 27], "unique_cluster_label": 14, "unit": [0, 1, 3, 4, 5, 10, 12, 18, 24, 27, 28, 29, 30], "unitari": [5, 6, 21, 28, 29], "unitarili": [21, 27], "uniti": 24, "univari": 24, "univers": [0, 1, 2, 13, 20, 22, 23, 25, 27, 28, 29, 30], "unix": 1, "unknow": [0, 21, 27], "unknown": [0, 1, 3, 4, 5, 6, 8, 10, 13, 21, 22, 27, 28, 29, 30], "unknowwn": 12, "unlabel": 1, "unless": [0, 3, 6, 11, 13, 22, 27, 29], "unlik": [1, 3, 8, 13, 29, 30], "unnecessarili": 9, "unord": 3, "unpublish": 30, "unravel": 1, "unrol": [3, 11], "unseen": [0, 7, 9, 15], "unstabl": 1, "unsupervis": [0, 1, 4, 12, 20, 27], "unsymmetr": [21, 27], "until": [1, 2, 4, 9, 12, 13, 14, 29], "untouch": 0, "unusu": 12, "up": [1, 3, 4, 5, 6, 8, 10, 11, 13, 14, 16, 18, 19, 20, 21, 22, 24, 25, 30], "updat": [1, 2, 10, 12, 13, 14, 15, 18], "uploa": 27, "upload": [15, 20, 22, 26], "upon": [0, 1, 6, 7, 11, 21], "upper": [0, 8, 9, 16, 21, 28], "uppercas": [21, 27], "upsampl": 4, "upscal": 4, "url": [27, 28], "us": [4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 17, 19, 21, 24, 26], "usag": [0, 8, 20, 27, 28, 30], "usd": [], "usd10000": [], "use_bia": 4, "usecol": [0, 27], "useless": 1, "user": [0, 1, 2, 4, 6, 7, 15, 20, 21, 22, 27, 28], "usernam": [15, 22], "usetex": 24, "usg": 6, "usr": 24, "usual": [0, 3, 4, 7, 12, 13, 14, 27, 30], "ut": 5, "util": [1, 3, 4, 6, 7, 10, 14, 19, 27], "ux": 21, "v": [2, 4, 5, 6, 11, 13, 15, 20, 28, 29], "v0": 24, "v1": 24, "v2": 24, "v_": 30, "v_0": [11, 30], "v_t": 30, "va": 1, "vahid": 27, "val": 13, "val_accuraci": 3, "val_loss": 4, "vale": 2, "valid": [0, 1, 4, 7, 9, 10, 13, 20, 24, 27, 28, 30], "validation_data": 3, "validation_split": 4, "valu": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 20, 21, 22, 27, 30], "valuat": 9, "valy": 4, "van": [0, 19, 22, 27, 28, 29, 30], "vandenbergh": [8, 13, 29], "vandermond": [0, 27], "vanilla": [0, 6, 11, 14, 28, 30], "vanish": [1, 4, 13, 24, 29], "var": [5, 6, 10, 11, 19, 22, 24, 28], "var_x": 24, "varabl": 8, "varepsilon": [5, 6, 19], "varepsilon_": [5, 6], "varepsilon_i": [5, 6], "vari": [0, 1, 3, 5, 6, 10, 27], "variabl": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 14, 21, 27, 28, 30], "varianc": [0, 1, 5, 7, 9, 10, 11, 13, 14, 18, 20, 21, 24, 27, 28, 29, 30], "variance_i": [5, 11, 28], "variance_x": [5, 11, 28], "variant": [0, 1, 6, 8, 12, 13, 27, 28, 29, 30], "variat": [3, 4, 11, 27], "varieti": [0, 3, 12, 20, 22, 27], "variou": [1, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 19, 20, 21, 22, 24, 27, 28, 29, 30], "varydimens": 4, "vastli": 3, "vaue": 1, "vault": 0, "vdot": [2, 13, 29, 30], "ve": [22, 30], "vec": 6, "vector": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 17, 18, 20, 29, 30], "vector_mean": 14, "ventur": [0, 8, 20, 27], "venv": 15, "verbos": [1, 3, 4], "veri": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 22, 24, 26, 27, 28, 29, 30], "verifi": [3, 11, 21, 27], "versatil": [8, 27], "versicolor": [8, 9], "version": [0, 3, 10, 13, 14, 15, 20, 21, 22, 24, 27], "versu": 1, "vert": [0, 1, 5, 6, 7, 8, 9, 11, 13, 16, 17, 27, 28, 29, 30], "vert_1": [5, 6, 28, 29, 30], "vert_2": [5, 6, 11, 17, 28, 29, 30], "via": [0, 5, 6, 7, 8, 9, 10, 11, 12, 19, 20, 21, 22, 23, 24, 25, 27, 28, 29, 30], "vidal": 11, "video": [0, 1, 12, 20, 23, 25, 27, 28, 29], "view": [1, 3, 5, 6, 12, 13, 24, 26, 27, 29, 30], "violat": 8, "virginica": 9, "viridi": [0, 1, 2, 3, 27], "virtual": 1, "viscos": 13, "viscou": 13, "visibl": 15, "vision": [0, 3], "visual": [0, 3, 11, 12, 18, 20, 27, 28], "visualis": 1, "visualstudio": [15, 16], "viz": [6, 8, 24], "vmap": 13, "vmax": [1, 6], "vmh0zpt0tli": 30, "vmin": [1, 6], "voic": 3, "volatil": 30, "volum": [0, 3, 27], "vote": [10, 27], "voting_clf": 10, "votingclassifi": 10, "votingsimpl": 10, "vstack": [5, 11, 21, 24, 27, 28], "vt": [5, 28, 29], "w": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 21, 24, 27, 28, 29, 30], "w1": 8, "w2": [8, 11], "w3": 8, "w_": [1, 12], "w_1": [8, 21], "w_1x_": 8, "w_1x_1": 8, "w_2": [8, 21], "w_2x_": 8, "w_2x_2": 8, "w_3": 21, "w_4": 21, "w_hidden": 2, "w_i": [1, 2, 10], "w_ix_i": 12, "w_j": 21, "w_m": 21, "w_output": 2, "w_px_": 8, "w_px_p": 8, "w_t": [], "wa": [1, 3, 4, 5, 6, 7, 10, 11, 12, 14, 17, 21, 27, 28, 30], "wai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 18, 19, 21, 24, 27, 28, 29, 30], "walk": 9, "walker": 24, "wang": [0, 27], "want": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 20, 22, 24, 27, 28, 29, 30], "warn": 4, "warrant": 6, "wast": [3, 30], "watch": [20, 29, 30], "wave": 3, "wavelet": 8, "we": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29], "weak": [9, 10, 14], "weather": [1, 12], "web": [20, 23, 25, 27], "webpag": 27, "websit": [6, 21, 22, 23, 27], "wedg": [8, 24], "wednesdai": [25, 27], "wee": 11, "week": [0, 5, 6, 7, 22, 23, 25], "weekli": [15, 16, 20, 22, 23, 25, 26, 27], "weight": [1, 2, 3, 6, 7, 9, 10, 12, 13, 18, 24, 30], "weigth": 2, "welcom": [8, 15, 20], "well": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 20, 21, 22, 24, 26, 27, 28, 29, 30], "went": 8, "were": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 24, 27], "wessel": [0, 19, 22, 27, 28, 29, 30], "what": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 24, 30], "whatev": 3, "when": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 24, 27, 28, 29], "whenev": [13, 15, 24, 30], "where": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 25, 27, 28, 29, 30], "wherea": [6, 24, 30], "wherefrom": 22, "wherein": [1, 12], "whether": [0, 3, 5, 7, 9, 22, 24, 27], "which": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 29], "whichev": [1, 3], "while": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 19, 24, 27, 28, 29], "white": 9, "whiteboad": 30, "whiteboard": [28, 29], "who": [0, 15], "whole": [1, 3, 4, 5, 9, 11, 13, 30], "whose": [0, 6, 10, 24, 28], "whow": [11, 28], "why": [0, 1, 3, 6, 13, 15, 16, 17, 19, 22, 28, 29], "wide": [0, 1, 3, 6, 7, 12, 20, 21, 22, 27], "widehat": 6, "width": [0, 3, 8, 9, 27], "wieringen": [0, 19, 22, 27, 28, 29, 30], "wiki": 22, "wikipedia": 22, "win": 10, "wind": 9, "wing": [25, 27], "winther": 2, "wiothout": 6, "wiscons": 7, "wisconsin": 10, "wisdom": [6, 28, 30], "wise": [1, 5, 12, 13, 28, 29, 30], "wish": [0, 2, 5, 7, 8, 11, 13, 14, 18, 21, 22, 27, 28, 29, 30], "with_std": [0, 28], "wither": 6, "within": [0, 2, 3, 4, 7, 9, 12, 13, 14, 24, 26, 27, 29], "withinclust": 14, "without": [0, 1, 5, 6, 8, 9, 11, 12, 13, 15, 18, 22, 27, 28, 29, 30], "won": [0, 15, 27], "wonder": 8, "word": [0, 1, 3, 4, 5, 6, 7, 14, 24, 27, 28, 29, 30], "work": [0, 1, 4, 6, 7, 8, 9, 13, 15, 16, 18, 20, 22, 23, 24, 25, 27, 28, 30], "workabl": 30, "workshop": 27, "world": [0, 8, 16, 28], "worldwid": [0, 27], "worri": 15, "wors": [0, 1, 3, 4, 6, 27], "worth": 9, "worthi": 22, "would": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 18, 21, 22, 24, 27, 28, 29, 30], "wrap": [6, 21, 27], "write": [0, 1, 2, 3, 5, 6, 7, 8, 12, 13, 15, 16, 18, 21, 27, 28, 30], "written": [0, 2, 3, 5, 11, 12, 13, 16, 20, 21, 22, 24, 27, 28, 29, 30], "wrong": [1, 8, 15], "wrongli": 10, "wrote": [5, 11, 28], "wrt": [10, 13, 30], "wth": [10, 13, 30], "www": [20, 21, 22, 26, 27, 29, 30], "wx_1": 8, "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 27, 29, 30], "x0": 8, "x1": [4, 8, 9, 10, 13], "x1_exampl": 8, "x1d": 8, "x2": [8, 9, 10, 13], "x2d": [8, 11], "x2d_train": 11, "x2dsl": 11, "x3": 8, "x_": [0, 2, 3, 5, 6, 8, 10, 11, 13, 14, 21, 24, 27, 28, 29, 30], "x_0": [0, 5, 11, 18, 21, 27, 28], "x_1": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 18, 21, 24, 27, 28, 29, 30], "x_2": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 21, 24, 27, 28, 29], "x_3": [8, 21, 24], "x_4": 21, "x_6": 18, "x_center": 11, "x_data": 1, "x_data_ful": 1, "x_hidden": 2, "x_i": [0, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 24, 27, 28, 29, 30], "x_input": 2, "x_ix_": [0, 27], "x_iy_i": 8, "x_j": [0, 2, 8, 9, 12, 16, 24, 28, 30], "x_jy_j": 8, "x_k": [12, 14, 21, 24, 28], "x_l": 24, "x_m": [6, 12, 21, 24], "x_mean": [18, 30], "x_n": [0, 2, 3, 6, 8, 11, 12, 13, 21, 24, 27, 29], "x_new": [9, 10], "x_norm": [18, 30], "x_offset": [6, 28, 30], "x_output": 2, "x_p": [3, 7, 9], "x_poli": 9, "x_poly10": 9, "x_pred": 4, "x_prev": 2, "x_reduc": 11, "x_sampl": 19, "x_scale": 8, "x_small": 13, "x_std": [18, 30], "x_t": 30, "x_test": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30], "x_test_": 17, "x_test_own": 6, "x_test_scal": [0, 6, 7, 9, 10, 11, 28, 30], "x_tot": 4, "x_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "x_train_": 17, "x_train_mean": [6, 28, 30], "x_train_own": 6, "x_train_scal": [0, 6, 7, 9, 10, 11, 28, 30], "x_val": 1, "xarrai": [20, 27], "xavier": 1, "xbnew": [13, 29, 30], "xcode": [0, 20, 22, 27], "xdclassiffierconfus": 10, "xdclassiffierroc": 10, "xg_clf": 10, "xgb": 10, "xgbclassifi": 10, "xgboost": 9, "xgboot": 10, "xgbregressor": 10, "xgparam": 10, "xgtree": 10, "xi": [8, 13, 30], "xi_": 8, "xi_1": 8, "xi_i": 8, "xk": 8, "xla": [13, 20, 27], "xlabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 24, 27, 28, 29, 30], "xlim": [6, 10], "xm": 9, "xmesh": 13, "xnew": [0, 13, 27, 29, 30], "xp": 24, "xpanda": [0, 28], "xpd": [5, 11, 28], "xplot": 0, "xscale": [0, 28], "xsr": 9, "xt_x": [13, 29, 30], "xtest": 6, "xtick": [3, 6, 8, 9], "xtrain": 6, "xu": [0, 27], "xx": [0, 21, 27], "xy": [0, 6, 8, 21, 27], "xytext": 8, "xz": [21, 27], "y": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "y1": 4, "y2": 4, "y3": 4, "y_": [0, 1, 5, 6, 10, 11, 21, 27, 28], "y_0": [0, 5, 11, 21, 27, 28], "y_1": [0, 5, 8, 9, 11, 13, 21, 27, 28, 29, 30], "y_1y_1": 8, "y_1y_1k": 8, "y_1y_2": 8, "y_1y_2k": 8, "y_1y_n": 8, "y_1y_nk": 8, "y_2": [0, 5, 8, 9, 11, 21, 27, 28], "y_2y_1": 8, "y_2y_1k": 8, "y_2y_2": 8, "y_2y_2k": 8, "y_3": [0, 9, 21], "y_4": 21, "y_center": [18, 30], "y_data": [0, 1, 5, 6, 27, 28, 29, 30], "y_data_ful": 1, "y_decis": 8, "y_fit": [0, 28], "y_i": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 19, 21, 22, 27, 28, 29, 30], "y_if_": 10, "y_ix_": [0, 27], "y_ix_i": [7, 8, 13, 28, 29, 30], "y_iy_jk": 8, "y_j": [6, 8, 12, 22], "y_k": 12, "y_m": 21, "y_mean": [18, 30], "y_model": [0, 4, 5, 6, 27, 28, 29, 30], "y_n": [8, 13, 29, 30], "y_ny_1": 8, "y_ny_1k": 8, "y_ny_2": 8, "y_ny_2k": 8, "y_ny_n": 8, "y_ny_nk": 8, "y_offset": [6, 17, 28, 30], "y_plot": 9, "y_pred": [0, 1, 4, 6, 7, 8, 9, 10, 28, 30], "y_pred1": 9, "y_pred2": 9, "y_pred_rf": 10, "y_pred_tre": 10, "y_proba": [7, 10], "y_sampl": 19, "y_scaler": [6, 28, 30], "y_test": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30], "y_test_onehot": 1, "y_test_predict": [], "y_tot": 4, "y_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "y_train_mean": [6, 28, 30], "y_train_onehot": 1, "y_train_predict": [], "y_train_scal": [6, 28, 30], "y_val": 1, "ye": [3, 6, 7], "year": [0, 20, 27], "yet": [0, 1, 6, 8, 11, 13, 27], "yi": [13, 30], "yield": [0, 2, 5, 6, 8, 10, 12, 13, 14, 21, 24, 27, 29, 30], "yk": 8, "ylabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 24, 27, 28, 29, 30], "ylim": [3, 6], "ym": 9, "ymesh": 13, "yn": 0, "yo": [8, 9, 10], "yoshua": [1, 26], "you": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30], "young": 0, "your": [1, 2, 4, 5, 6, 8, 11, 13, 15, 17, 19, 20, 21, 27, 29, 30], "your_model_object": 16, "yourself": [11, 13, 27, 29], "youtu": [28, 29], "youtub": [20, 29, 30], "ypred": 6, "ypredict": [0, 13, 27, 28, 29, 30], "ypredict2": [13, 29, 30], "ypredictlasso": [5, 29], "ypredictol": [0, 5, 29], "ypredictown": [6, 28, 30], "ypredictownridg": [6, 28, 29, 30], "ypredictridg": [0, 5, 6, 28, 29, 30], "ypredictskl": [6, 28, 30], "ytest": 6, "ytick": [3, 6, 8, 9], "ytild": [0, 6, 27, 28], "ytildelasso": [5, 29], "ytildenp": [0, 27, 28], "ytildeol": [0, 5, 29], "ytildeownridg": [6, 28, 29, 30], "ytilderidg": [5, 6, 28, 29, 30], "ytrain": 6, "yuxi": 27, "yx": [21, 27], "yy": [21, 27], "yz": [21, 27], "z": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 21, 24, 27, 28], "z_": [1, 2, 12, 21, 27], "z_0": [21, 27], "z_1": [21, 27], "z_2": [21, 27], "z_c": 1, "z_h": 1, "z_hidden": 2, "z_i": [1, 12], "z_j": [1, 12], "z_k": [12, 28], "z_m": 1, "z_mod": 9, "z_o": 1, "z_output": 2, "zaman": 24, "zaxi": 6, "zero": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "zeros_lik": 4, "zeroth": 28, "zfill": 4, "zip": [4, 6], "zm_h": [0, 27], "zn": [], "zone": [], "zoom": 27, "zx": [21, 27], "zy": [21, 27], "zz": [21, 27], "\u00f8yvind": [6, 28, 30]}, "titles": ["3. Linear Regression", "14. Building a Feed Forward Neural Network", "15. Solving Differential Equations with Deep Learning", "16. Convolutional Neural Networks", "17. Recurrent neural networks: Overarching view", "4. Ridge and Lasso Regression", "5. Resampling Methods", "6. Logistic Regression", "8. Support Vector Machines, overarching aims", "9. Decision trees, overarching aims", "10. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods", "11. Basic ideas of the Principal Component Analysis (PCA)", "13. Neural networks", "7. Optimization, the central part of any Machine Learning algortithm", "12. Clustering and Unsupervised Learning", "Exercises week 34", "Exercises week 35", "Exercises week 36", "Exercises week 37", "Exercises week 37", "Applied Data Analysis and Machine Learning", "2. Linear Algebra, Handling of Arrays and more Python Features", "Project 1 on Machine Learning, deadline October 6 (midnight), 2025", "Course setting", "1. Elements of Probability Theory and Statistical Data Analysis", "Teachers and Grading", "Textbooks", "Week 34: Introduction to the course, Logistics and Practicalities", "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression", "Week 36: Linear Regression and Gradient descent", "Week 37: Gradient descent methods"], "titleterms": {"": [8, 10, 29, 30], "1": [0, 15, 16, 17, 18, 19, 22, 28], "15": 19, "19": 19, "1a": 18, "2": [0, 15, 16, 17, 18, 19, 27, 28, 29], "2023": 25, "2025": 22, "2a": [], "2b": [], "3": [0, 15, 16, 17, 18, 19, 28], "34": [15, 27], "35": [16, 28], "36": [17, 29], "37": [18, 19, 30], "3a": 18, "3b": 18, "4": [0, 15, 16, 17, 18, 19, 28], "4a": 18, "4b": 18, "5": [0, 16, 18], "6": 22, "8": 30, "A": [0, 1, 4, 8, 9, 27], "And": [27, 28, 30], "But": 30, "In": 25, "Ising": 6, "The": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 15, 20, 27, 28, 29, 30], "To": 27, "With": [4, 29], "about": [27, 28, 29], "abov": 29, "accuraci": 30, "across": 30, "activ": [1, 12], "ad": [0, 6, 22, 27, 28], "adaboost": 10, "adagrad": [13, 30], "adam": [13, 30], "adapt": [10, 30], "adjust": 1, "advanc": 22, "adversari": 4, "again": [3, 9], "ai": [22, 27], "aim": [8, 9, 27], "aka": 27, "al": 30, "algebra": [21, 27], "algorithm": [9, 10, 11, 12, 27, 28, 29, 30], "algortithm": [13, 29], "all": 8, "an": [0, 4, 10, 15, 27], "analys": [5, 28, 29], "analysi": [0, 5, 6, 11, 20, 22, 24, 27, 28, 29], "analyt": [0, 16, 18], "ani": [13, 29], "anoth": [9, 29], "appli": 20, "approach": [0, 8, 14, 27, 30], "approxim": 12, "architectur": 1, "arrai": [21, 27], "assist": 25, "autocorrel": 24, "autograd": [2, 13, 30], "automat": [13, 30], "averag": 30, "b": 22, "back": [1, 11, 12, 28, 29], "background": [20, 22], "bag": 10, "base": [13, 30], "basic": [0, 5, 7, 9, 10, 11, 21, 28, 29], "batch": [1, 30], "bay": 5, "befor": 11, "better": 8, "bia": [6, 19, 22, 30], "binari": 1, "bind": 27, "bird": 10, "boldsymbol": [18, 28], "boost": 10, "bootstrap": [6, 10], "boston": [], "breast": 1, "brief": 27, "bring": 12, "build": [1, 3, 9], "c": [22, 27], "calcul": [18, 28, 29], "can": [27, 30], "cancer": [1, 7, 9, 11], "cart": 9, "case": [8, 10, 24, 28, 29], "central": [13, 20, 24, 29], "chain": 12, "challeng": 30, "chang": 10, "channel": 27, "chi": [0, 27], "choic": 17, "choos": [1, 30], "cifar01": 3, "classic": 11, "classif": [1, 9, 10], "classifi": 8, "clip": 1, "cluster": 14, "cnn": 3, "code": [1, 2, 5, 9, 11, 12, 13, 14, 15, 16, 22, 27, 28, 29, 30], "collect": [1, 3], "combin": 30, "commun": 27, "compar": [2, 10, 16], "comparison": 29, "compet": 30, "complet": 28, "complex": [0, 6, 22, 28], "complic": 6, "compon": 11, "comput": [9, 19, 30], "computerlab": 27, "con": [9, 30], "concept": 24, "condit": 29, "conjug": 13, "contn": 27, "converg": 30, "convex": [8, 13, 29], "convolut": [3, 12], "correct": 30, "correl": [11, 28], "correspond": [], "cost": [1, 10, 28, 29, 30], "cours": [20, 23, 26, 27], "covari": [5, 11, 24, 28], "cover": 27, "creat": 16, "cross": [6, 22], "cython": 27, "d": 22, "data": [0, 1, 3, 6, 7, 9, 11, 15, 17, 18, 20, 24, 27, 28], "dataset": [1, 3, 18], "david": 27, "deadlin": [22, 27], "deadllin": 25, "decai": [2, 30], "decis": [9, 10], "decomposit": [5, 11, 21, 28, 29], "deeep": [], "deep": [1, 2, 27], "defin": [1, 27], "degre": [0, 17, 28], "deliver": [15, 16], "deliveri": 22, "dens": 0, "deriv": [5, 12, 16, 17, 19, 28, 29, 30], "descent": [2, 10, 13, 18, 22, 29, 30], "design": 28, "detail": [3, 27], "develop": 1, "diagon": 11, "differ": [8, 30], "differenti": [2, 13, 30], "diffus": 2, "dimens": 30, "dimension": [2, 3, 8, 18], "disadvantag": 9, "discret": 24, "discrimin": 27, "distribut": [5, 24], "do": [1, 30], "doe": [28, 29], "domain": 24, "down": 1, "dropout": 1, "e": 22, "economi": [28, 29], "electron": 22, "element": [0, 24, 27], "elimin": 21, "energi": 27, "ensembl": 10, "entropi": 9, "environ": [0, 15], "equat": [0, 2, 12, 28, 29], "error": [0, 10, 27, 28, 29], "essenti": 27, "et": 30, "etc": 27, "euler": 2, "evalu": 1, "exampl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 27, 28, 29, 30], "exercis": [0, 6, 15, 16, 17, 18, 19, 28], "expect": [19, 24], "experi": 24, "explor": 0, "exponenti": [2, 30], "express": [16, 17, 19, 28], "extend": 29, "extrapol": 4, "extrem": [10, 27], "ey": 10, "f": 22, "fall": 25, "famili": [1, 27], "famou": 21, "fantast": [28, 29], "featur": [9, 16, 21, 28], "feed": [1, 12], "final": [12, 28, 30], "find": [16, 18], "fine": 1, "first": [4, 12, 27, 29], "fit": [0, 10, 15, 16, 27, 29], "fix": [28, 29, 30], "forc": 3, "forest": 10, "form": 18, "format": [22, 27], "formula": 18, "forward": [1, 2, 12], "foster": 27, "fourier": 3, "frank": 6, "freedom": [0, 17, 28], "frequent": [28, 30], "frequentist": [0, 27], "from": [5, 10, 12, 27, 28, 29, 30], "full": 2, "function": [0, 1, 6, 7, 8, 10, 11, 12, 13, 22, 24, 27, 28, 29, 30], "further": [3, 5, 28, 29], "g": 22, "gan": 4, "gaussian": 21, "gd": [13, 30], "gener": [4, 9, 27], "geometr": [11, 29], "gini": 9, "github": 15, "goal": [15, 16, 17, 18, 19], "good": [0, 27], "goodfellow": 30, "grade": [25, 27], "gradient": [1, 2, 10, 13, 18, 22, 29, 30], "growth": 2, "h": 22, "ha": 20, "handl": [21, 27], "hessian": [28, 29, 30], "hidden": 2, "hous": [], "how": 16, "hyperparamet": [1, 17], "hyperplan": 8, "i": [0, 1, 27], "id3": 9, "idea": 11, "ideal": 29, "ii": 27, "illustr": 29, "implement": [1, 16, 17, 18], "implic": [5, 28, 29], "import": [5, 21, 27, 28, 29], "improv": [1, 30], "includ": [13, 22, 30], "increment": 11, "index": 9, "inform": 25, "input": 2, "instal": [20, 22, 27], "instructor": 25, "interpret": [5, 11, 27, 28, 29], "introduc": [11, 13, 28], "introduct": [0, 6, 20, 21, 22, 27], "invers": [5, 21], "invert": [28, 29], "iter": 10, "its": 28, "jacobian": 28, "jax": 13, "julia": 27, "jungl": 10, "kera": [1, 3], "kernel": [8, 11], "lab": [29, 30], "lagrangian": 8, "lasso": [5, 6, 22, 28, 29], "last": [28, 30], "later": [5, 28, 29], "layer": [1, 2, 3, 12], "learn": [0, 1, 2, 11, 13, 14, 15, 16, 17, 18, 19, 20, 22, 27, 28, 29, 30], "least": [5, 6, 16, 19, 22, 27, 28, 29, 30], "lectur": [27, 29, 30], "level": 10, "librari": [20, 27], "likelihood": 7, "limit": [1, 13, 24, 29, 30], "linear": [0, 8, 13, 15, 21, 27, 28, 29], "link": [5, 11, 26, 28], "literatur": 22, "logist": [7, 27], "loss": [28, 29, 30], "lu": 21, "machin": [0, 8, 13, 20, 22, 27, 29], "main": [24, 27], "make": [0, 9, 10, 28], "mani": [10, 12], "mass": 27, "materi": [22, 27, 28, 29, 30], "math": [5, 28, 29], "mathemat": [3, 5, 8, 28, 29], "matric": [5, 21, 27], "matrix": [1, 5, 11, 12, 16, 21, 27, 28, 29, 30], "matter": 0, "max": 28, "mean": [0, 28, 29], "meet": [5, 10, 24, 27, 28], "mercer": 8, "method": [6, 9, 10, 13, 22, 27, 29, 30], "midnight": 22, "min": 28, "mini": 30, "minibatch": 30, "minim": 27, "ml": 27, "mlp": 12, "mnist": [3, 4], "model": [0, 1, 4, 6, 12, 15, 17, 27], "moment": 30, "momentum": [13, 22, 30], "mondai": [29, 30], "moon": [8, 9], "more": [3, 6, 21, 22, 27, 28, 29, 30], "motiv": 30, "move": 30, "multilay": 12, "multipl": [1, 3, 17], "multipli": 8, "need": [22, 27], "network": [1, 2, 3, 4, 7, 12, 27], "neural": [1, 2, 3, 4, 7, 12, 27], "new": [4, 18], "newton": [29, 30], "non": 8, "none": 30, "normal": [0, 1], "notat": 12, "note": [22, 28, 29], "now": [1, 9, 13, 29, 30], "nuclear": [0, 27], "numba": 27, "number": [0, 2, 24, 28, 30], "numer": [2, 22, 24], "numpi": [21, 27], "object": 3, "obtain": 11, "octob": 22, "od": 2, "off": [6, 19, 22], "ol": [5, 6, 15, 16, 18, 22, 29], "one": [2, 12, 18, 29], "oper": 21, "optim": [1, 8, 13, 18, 20, 27, 28, 29, 30], "order": [13, 18, 30], "ordinari": [5, 6, 16, 19, 22, 27, 28, 29, 30], "organ": [0, 27], "oslo": 26, "other": [4, 9, 11, 12, 21, 22, 27], "our": [0, 4, 5, 11, 13, 22, 27, 28, 29], "outcom": [20, 27], "output": 2, "overarch": [0, 4, 8, 9, 27, 28], "overview": [10, 27, 30], "own": [0, 10, 11, 22, 27, 28], "packag": [21, 27], "panda": [27, 28], "paramet": [27, 28], "paramt": 18, "part": [13, 20, 22, 29], "partial": 2, "pass": 1, "pca": 11, "pdf": 24, "perceptron": 12, "perform": [1, 9], "period": 3, "perspect": 1, "plan": [28, 29, 30], "plethora": 27, "point": 4, "poisson": 2, "polynomi": [3, 16, 18, 29], "popul": 2, "popular": 27, "practic": [13, 25, 27, 30], "pre": [1, 3], "preambl": 22, "predict": 4, "preprocess": [28, 30], "prerequisit": [3, 20, 27], "princip": 11, "principl": 3, "pro": [9, 30], "probabl": [5, 24], "problem": [1, 2, 13, 27, 28, 29, 30], "procedur": [9, 27], "process": [1, 3], "program": [2, 13, 22, 29, 30], "project": [6, 22, 25, 27], "prop": 13, "propag": [1, 12], "properti": [5, 24, 28, 29, 30], "python": [0, 9, 15, 20, 21, 27], "quick": 8, "r": 27, "random": [10, 11, 24], "raphson": 29, "rate": [22, 30], "read": [9, 27, 28, 30], "real": [6, 27], "recommend": [27, 28], "recurr": [4, 12], "reduc": [0, 28], "reduct": 3, "refer": 22, "reformul": 2, "regress": [0, 5, 6, 7, 9, 10, 13, 15, 17, 18, 19, 22, 27, 28, 29, 30], "regular": 1, "relat": [], "relev": [26, 28], "relu": 1, "remark": 3, "remind": [6, 8, 27, 28, 29, 30], "replac": [13, 30], "report": 22, "repositori": 15, "requir": [2, 20], "resampl": [6, 19, 22], "rescal": [6, 28], "residu": [28, 29], "resourc": 2, "result": [28, 29], "revisit": [13, 29, 30], "rewrit": [27, 28], "ridg": [0, 5, 6, 17, 18, 19, 22, 28, 29, 30], "rm": 13, "rmsprop": 30, "rule": [12, 30], "rung": 22, "same": [13, 30], "sampl": 11, "scale": [17, 18, 28, 30], "schedul": 27, "schemat": 9, "scheme": 2, "scienc": 27, "scikit": [0, 1, 11, 27, 28, 29, 30], "second": [13, 18, 30], "semest": 25, "sensit": 29, "septemb": [19, 29, 30], "session": [29, 30], "set": [0, 2, 3, 9, 12, 15, 23, 27, 28, 29], "setup": 15, "sgd": [13, 30], "should": 1, "similar": [13, 30], "simpl": [0, 4, 9, 13, 18, 27, 28, 29, 30], "simplest": 18, "singl": 10, "singular": [5, 11, 28, 29], "size": [28, 29, 30], "sklearn": 16, "slightli": 30, "sneak": 30, "soft": 8, "softmax": 1, "softwar": [22, 27], "solv": [2, 29], "solver": 13, "some": [13, 21, 28, 29], "specifi": 2, "split": [0, 15, 28], "squar": [0, 5, 6, 10, 16, 19, 22, 27, 28, 29, 30], "standard": [13, 28], "state": 0, "statist": [5, 6, 20, 24, 27], "steepest": [10, 13, 29], "step": 30, "stochast": [13, 22, 24, 30], "stop": 30, "strongli": 27, "suggest": 27, "summari": [25, 27], "superposit": 3, "supervis": 1, "support": 8, "svd": [5, 28, 29], "synthet": 18, "systemat": 3, "t": 28, "take": 16, "taken": [27, 30], "teach": 25, "teacher": [25, 27], "technic": 28, "techniqu": [6, 11, 22], "technologi": 20, "tensorflow": [1, 3], "tent": [25, 27], "test": [0, 1, 15, 17, 28], "text": 27, "textbook": [26, 27], "than": 29, "theorem": [5, 8, 11, 12, 24], "theori": 24, "theta": 18, "thi": 27, "time": 30, "tip": [13, 30], "togeth": 12, "tool": [22, 27], "top": 1, "topic": 27, "toward": 11, "trade": [6, 19, 22], "tradeoff": 6, "train": [0, 1, 4, 15, 27, 28], "transform": 3, "tree": [9, 10], "tuesdai": 29, "tune": 1, "two": [3, 8, 20], "type": [2, 4, 12, 27], "uio": 27, "univers": [12, 26], "unsupervis": 14, "up": [0, 2, 9, 12, 15, 27, 28, 29], "updat": [22, 30], "us": [0, 1, 2, 3, 7, 13, 16, 18, 20, 22, 27, 28, 29, 30], "v": [3, 30], "valid": [6, 22], "valu": [5, 11, 19, 24, 28, 29], "vari": 30, "variabl": [24, 29], "varianc": [6, 19, 22], "variou": 0, "vector": [8, 12, 16, 21, 27, 28], "versu": 27, "video": 30, "view": [0, 4, 10, 28], "virtual": 15, "visual": [1, 9], "wai": [9, 22], "wave": 2, "we": [27, 30], "wednesdai": 29, "week": [15, 16, 17, 18, 19, 27, 28, 29, 30], "weekli": [], "what": [0, 27, 28, 29], "when": 30, "which": [1, 30], "why": [27, 30], "wisconsin": 7, "write": [4, 11, 22, 29], "x": 28, "xgboost": 10, "yet": 29, "your": [0, 10, 16, 18, 22, 28]}}) \ No newline at end of file +Search.setIndex({"alltitles": {"1a)": [[18, "a"]], "3a)": [[18, "id1"]], "3b)": [[18, "b"]], "4a)": [[18, "id2"]], "4b)": [[18, "id3"]], "A Classification Tree": [[9, "a-classification-tree"]], "A Frequentist approach to data analysis": [[0, "a-frequentist-approach-to-data-analysis"], [27, "a-frequentist-approach-to-data-analysis"]], "A better approach": [[8, "a-better-approach"]], "A first summary": [[27, "a-first-summary"]], "A quick Reminder on Lagrangian Multipliers": [[8, "a-quick-reminder-on-lagrangian-multipliers"]], "A simple example": [[4, "a-simple-example"]], "A soft classifier": [[8, "a-soft-classifier"]], "A top-down perspective on Neural networks": [[1, "a-top-down-perspective-on-neural-networks"]], "ADAM algorithm, taken from Goodfellow et al": [[30, "adam-algorithm-taken-from-goodfellow-et-al"]], "ADAM optimizer": [[13, "adam-optimizer"], [30, "id2"]], "Accuracy": [[30, "accuracy"]], "Activation functions": [[12, "activation-functions"]], "AdaGrad Properties": [[30, "adagrad-properties"]], "AdaGrad Update Rule Derivation": [[30, "adagrad-update-rule-derivation"]], "AdaGrad algorithm, taken from Goodfellow et al": [[30, "adagrad-algorithm-taken-from-goodfellow-et-al"]], "Adam Optimizer": [[30, "adam-optimizer"]], "Adam vs. AdaGrad and RMSProp": [[30, "adam-vs-adagrad-and-rmsprop"]], "Adam: Bias Correction": [[30, "adam-bias-correction"]], "Adam: Exponential Moving Averages (Moments)": [[30, "adam-exponential-moving-averages-moments"]], "Adam: Update Rule Derivation": [[30, "adam-update-rule-derivation"]], "Adaptive boosting: AdaBoost, Basic Algorithm": [[10, "adaptive-boosting-adaboost-basic-algorithm"]], "Adaptivity Across Dimensions": [[30, "adaptivity-across-dimensions"]], "Adding error analysis and training set up": [[27, "adding-error-analysis-and-training-set-up"], [28, "adding-error-analysis-and-training-set-up"]], "Adjust hyperparameters": [[1, "adjust-hyperparameters"]], "Algorithms and codes for Adagrad, RMSprop and Adam": [[30, "algorithms-and-codes-for-adagrad-rmsprop-and-adam"]], "Algorithms for Setting up Decision Trees": [[9, "algorithms-for-setting-up-decision-trees"]], "An Overview of Ensemble Methods": [[10, "an-overview-of-ensemble-methods"]], "An extrapolation example": [[4, "an-extrapolation-example"]], "An optimization/minimization problem": [[27, "an-optimization-minimization-problem"]], "And finally \\boldsymbol{X}\\boldsymbol{X}^T": [[28, "and-finally-boldsymbol-x-boldsymbol-x-t"]], "And finally ADAM": [[30, "and-finally-adam"]], "And what about using neural networks?": [[27, "and-what-about-using-neural-networks"]], "Another Example, now with a polynomial fit": [[29, "another-example-now-with-a-polynomial-fit"]], "Another example, the moons again": [[9, "another-example-the-moons-again"]], "Applied Data Analysis and Machine Learning": [[20, null]], "Autocorrelation function": [[24, "autocorrelation-function"]], "Automatic differentiation": [[13, "automatic-differentiation"]], "Back to Ridge and LASSO Regression": [[28, "back-to-ridge-and-lasso-regression"], [29, "back-to-ridge-and-lasso-regression"]], "Back to the Cancer Data": [[11, "back-to-the-cancer-data"]], "Background literature": [[22, "background-literature"]], "Bagging": [[10, "bagging"]], "Bagging Examples": [[10, "bagging-examples"]], "Basic Matrix Features": [[21, "basic-matrix-features"]], "Basic ideas of the Principal Component Analysis (PCA)": [[11, null]], "Basic math of the SVD": [[5, "basic-math-of-the-svd"], [28, "basic-math-of-the-svd"], [29, "basic-math-of-the-svd"]], "Basics": [[7, "basics"]], "Basics of a tree": [[9, "basics-of-a-tree"]], "Batch Normalization": [[1, "batch-normalization"]], "Batches and mini-batches": [[30, "batches-and-mini-batches"]], "Bayes\u2019 Theorem and Ridge and Lasso Regression": [[5, "bayes-theorem-and-ridge-and-lasso-regression"]], "Boosting, a Bird\u2019s Eye View": [[10, "boosting-a-bird-s-eye-view"]], "Bootstrap": [[6, "bootstrap"]], "Bringing it together, first back propagation equation": [[12, "bringing-it-together-first-back-propagation-equation"]], "Building a Feed Forward Neural Network": [[1, null]], "Building a tree, regression": [[9, "building-a-tree-regression"]], "Building neural networks in Tensorflow and Keras": [[1, "building-neural-networks-in-tensorflow-and-keras"]], "But none of these can compete with Newton\u2019s method": [[30, "but-none-of-these-can-compete-with-newton-s-method"]], "CNNs in more detail, building convolutional neural networks in Tensorflow and Keras": [[3, "cnns-in-more-detail-building-convolutional-neural-networks-in-tensorflow-and-keras"]], "Cancer Data again now with Decision Trees and other Methods": [[9, "cancer-data-again-now-with-decision-trees-and-other-methods"]], "Challenge: Choosing a Fixed Learning Rate": [[30, "challenge-choosing-a-fixed-learning-rate"]], "Choose cost function and optimizer": [[1, "choose-cost-function-and-optimizer"]], "Classical PCA Theorem": [[11, "classical-pca-theorem"]], "Clustering and Unsupervised Learning": [[14, null]], "Code for SVD and Inversion of Matrices": [[5, "code-for-svd-and-inversion-of-matrices"]], "Code with a Number of Minibatches which varies": [[30, "code-with-a-number-of-minibatches-which-varies"]], "Codes and Approaches": [[14, "codes-and-approaches"]], "Codes for the SVD": [[5, "codes-for-the-svd"], [28, "codes-for-the-svd"], [29, "codes-for-the-svd"]], "Coding Setup and Linear Regression": [[15, "coding-setup-and-linear-regression"]], "Collect and pre-process data": [[1, "collect-and-pre-process-data"]], "Communication channels": [[27, "communication-channels"]], "Compare Bagging on Trees with Random Forests": [[10, "compare-bagging-on-trees-with-random-forests"]], "Comparing with a numerical scheme": [[2, "comparing-with-a-numerical-scheme"]], "Comparison with OLS": [[29, "comparison-with-ols"]], "Computation of gradients": [[30, "computation-of-gradients"]], "Computing the Gini index": [[9, "computing-the-gini-index"]], "Conditions on convex functions": [[29, "conditions-on-convex-functions"]], "Conjugate gradient method": [[13, "conjugate-gradient-method"]], "Convergence rates": [[30, "convergence-rates"]], "Convex function": [[29, "convex-function"]], "Convex functions": [[13, "convex-functions"], [29, "convex-functions"]], "Convolution Examples: Polynomial multiplication": [[3, "convolution-examples-polynomial-multiplication"]], "Convolution Examples: Principle of Superposition and Periodic Forces (Fourier Transforms)": [[3, "convolution-examples-principle-of-superposition-and-periodic-forces-fourier-transforms"]], "Convolutional Neural Network": [[12, "convolutional-neural-network"]], "Convolutional Neural Networks": [[3, null]], "Correlation Function and Design/Feature Matrix": [[28, "correlation-function-and-design-feature-matrix"]], "Correlation Matrix": [[11, "correlation-matrix"], [28, "correlation-matrix"]], "Correlation Matrix with Pandas": [[28, "correlation-matrix-with-pandas"]], "Course Format": [[27, "course-format"]], "Course setting": [[23, null]], "Covariance Matrix Examples": [[28, "covariance-matrix-examples"]], "Covariance and Correlation Matrix": [[28, "covariance-and-correlation-matrix"]], "Cross-validation": [[6, "cross-validation"]], "Deadlines for projects (tentative)": [[27, "deadlines-for-projects-tentative"]], "Decision trees, overarching aims": [[9, null]], "Deep learning methods": [[27, "deep-learning-methods"]], "Define model and architecture": [[1, "define-model-and-architecture"]], "Defining the cost function": [[1, "defining-the-cost-function"]], "Deliverables": [[15, "deliverables"], [16, "deliverables"]], "Derivation of the AdaGrad Algorithm": [[30, "derivation-of-the-adagrad-algorithm"]], "Derivatives and the chain rule": [[12, "derivatives-and-the-chain-rule"]], "Derivatives, example 1": [[28, "derivatives-example-1"]], "Deriving OLS from a probability distribution": [[5, "deriving-ols-from-a-probability-distribution"]], "Deriving and Implementing Ordinary Least Squares": [[16, "deriving-and-implementing-ordinary-least-squares"]], "Deriving and Implementing Ridge Regression": [[17, "deriving-and-implementing-ridge-regression"]], "Deriving the Lasso Regression Equations": [[28, "deriving-the-lasso-regression-equations"], [29, "deriving-the-lasso-regression-equations"], [29, "id6"]], "Deriving the Ridge Regression Equations": [[28, "deriving-the-ridge-regression-equations"], [29, "deriving-the-ridge-regression-equations"], [29, "id3"]], "Deriving the back propagation code for a multilayer perceptron model": [[12, "deriving-the-back-propagation-code-for-a-multilayer-perceptron-model"]], "Developing a code for doing neural networks with back propagation": [[1, "developing-a-code-for-doing-neural-networks-with-back-propagation"]], "Diagonalize the sample covariance matrix to obtain the principal components": [[11, "diagonalize-the-sample-covariance-matrix-to-obtain-the-principal-components"]], "Different kernels and Mercer\u2019s theorem": [[8, "different-kernels-and-mercer-s-theorem"]], "Disadvantages": [[9, "disadvantages"]], "Discriminative Modeling": [[27, "discriminative-modeling"]], "Domains and probabilities": [[24, "domains-and-probabilities"]], "Dropout": [[1, "dropout"]], "Economy-size SVD": [[28, "economy-size-svd"], [29, "economy-size-svd"]], "Elements of Probability Theory and Statistical Data Analysis": [[24, null]], "Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods": [[10, null]], "Entropy and the ID3 algorithm": [[9, "entropy-and-the-id3-algorithm"]], "Essential elements of ML": [[27, "essential-elements-of-ml"]], "Evaluate model performance on test data": [[1, "evaluate-model-performance-on-test-data"]], "Example 2": [[28, "example-2"]], "Example 3": [[28, "example-3"]], "Example 4": [[28, "example-4"]], "Example Matrix": [[28, "example-matrix"], [29, "example-matrix"]], "Example of discriminative modeling, taken from Generative Deep Learning by David Foster": [[27, "example-of-discriminative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of generative modeling, taken from Generative Deep Learning by David Foster": [[27, "example-of-generative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of own Standard scaling": [[28, "example-of-own-standard-scaling"]], "Example relevant for the exercises": [[28, "example-relevant-for-the-exercises"]], "Example: Exponential decay": [[2, "example-exponential-decay"]], "Example: Population growth": [[2, "example-population-growth"]], "Example: The diffusion equation": [[2, "example-the-diffusion-equation"]], "Example: binary classification problem": [[1, "example-binary-classification-problem"]], "Examples": [[27, "examples"]], "Examples of likelihood functions used in logistic regression and neural networks": [[7, "examples-of-likelihood-functions-used-in-logistic-regression-and-neural-networks"]], "Exercise 1 - Choice of model and degrees of freedom": [[17, "exercise-1-choice-of-model-and-degrees-of-freedom"]], "Exercise 1 - Finding the derivative of Matrix-Vector expressions": [[16, "exercise-1-finding-the-derivative-of-matrix-vector-expressions"]], "Exercise 1 - Github Setup": [[15, "exercise-1-github-setup"]], "Exercise 1, scale your data": [[18, "exercise-1-scale-your-data"]], "Exercise 1: Expectation values for ordinary least squares expressions": [[19, "exercise-1-expectation-values-for-ordinary-least-squares-expressions"]], "Exercise 1: Setting up various Python environments": [[0, "exercise-1-setting-up-various-python-environments"]], "Exercise 2 - Deriving the expression for OLS": [[16, "exercise-2-deriving-the-expression-for-ols"]], "Exercise 2 - Deriving the expression for Ridge Regression": [[17, "exercise-2-deriving-the-expression-for-ridge-regression"]], "Exercise 2 - Setting up a Github repository": [[15, "exercise-2-setting-up-a-github-repository"]], "Exercise 2, calculate the gradients": [[18, "exercise-2-calculate-the-gradients"]], "Exercise 2: Expectation values for Ridge regression": [[19, "exercise-2-expectation-values-for-ridge-regression"]], "Exercise 2: making your own data and exploring scikit-learn": [[0, "exercise-2-making-your-own-data-and-exploring-scikit-learn"]], "Exercise 3 - Creating feature matrix and implementing OLS using the analytical expression": [[16, "exercise-3-creating-feature-matrix-and-implementing-ols-using-the-analytical-expression"]], "Exercise 3 - Fitting an OLS model to data": [[15, "exercise-3-fitting-an-ols-model-to-data"]], "Exercise 3 - Scaling data": [[17, "exercise-3-scaling-data"]], "Exercise 3 - Setting up a Python virtual environment": [[15, "exercise-3-setting-up-a-python-virtual-environment"]], "Exercise 3, using the analytical formulae for OLS and Ridge regression to find the optimal paramters \\boldsymbol{\\theta}": [[18, "exercise-3-using-the-analytical-formulae-for-ols-and-ridge-regression-to-find-the-optimal-paramters-boldsymbol-theta"]], "Exercise 3: Deriving the expression for the Bias-Variance Trade-off": [[19, "exercise-3-deriving-the-expression-for-the-bias-variance-trade-off"]], "Exercise 3: Normalizing our data": [[0, "exercise-3-normalizing-our-data"]], "Exercise 4 - Fitting a polynomial": [[16, "exercise-4-fitting-a-polynomial"]], "Exercise 4 - Implementing Ridge Regression": [[17, "exercise-4-implementing-ridge-regression"]], "Exercise 4 - Testing multiple hyperparameters": [[17, "exercise-4-testing-multiple-hyperparameters"]], "Exercise 4 - The train-test split": [[15, "exercise-4-the-train-test-split"]], "Exercise 4, Implementing the simplest form for gradient descent": [[18, "exercise-4-implementing-the-simplest-form-for-gradient-descent"]], "Exercise 4: Adding Ridge Regression": [[0, "exercise-4-adding-ridge-regression"]], "Exercise 4: Computing the Bias and Variance": [[19, "exercise-4-computing-the-bias-and-variance"]], "Exercise 5 - Comparing your code with sklearn": [[16, "exercise-5-comparing-your-code-with-sklearn"]], "Exercise 5, Ridge regression and a new Synthetic Dataset": [[18, "exercise-5-ridge-regression-and-a-new-synthetic-dataset"]], "Exercise 5: Analytical exercises": [[0, "exercise-5-analytical-exercises"]], "Exercise: Cross-validation as resampling techniques, adding more complexity": [[6, "exercise-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Exercise: Analysis of real data": [[6, "exercise-analysis-of-real-data"]], "Exercise: Bias-variance trade-off and resampling techniques": [[6, "exercise-bias-variance-trade-off-and-resampling-techniques"]], "Exercise: Lasso Regression on the Franke function with resampling": [[6, "exercise-lasso-regression-on-the-franke-function-with-resampling"]], "Exercise: Ordinary Least Square (OLS) on the Franke function": [[6, "exercise-ordinary-least-square-ols-on-the-franke-function"]], "Exercise: Ridge Regression on the Franke function with resampling": [[6, "exercise-ridge-regression-on-the-franke-function-with-resampling"]], "Exercises": [[0, "exercises"]], "Exercises and Projects": [[6, "exercises-and-projects"]], "Exercises week 34": [[15, null]], "Exercises week 35": [[16, null]], "Exercises week 36": [[17, null]], "Exercises week 37": [[18, null]], "Exercises week 38": [[19, null]], "Expectation values": [[24, "expectation-values"]], "Extending to more than one variable": [[29, "extending-to-more-than-one-variable"]], "Extremely useful tools, strongly recommended": [[27, "extremely-useful-tools-strongly-recommended"]], "Feed-forward neural networks": [[12, "feed-forward-neural-networks"]], "Feed-forward pass": [[1, "feed-forward-pass"]], "Final back propagating equation": [[12, "final-back-propagating-equation"]], "Fine-tuning neural network hyperparameters": [[1, "fine-tuning-neural-network-hyperparameters"]], "Fitting an Equation of State for Dense Nuclear Matter": [[0, "fitting-an-equation-of-state-for-dense-nuclear-matter"]], "Fixing the singularity": [[28, "fixing-the-singularity"], [29, "fixing-the-singularity"]], "Format for electronic delivery of report and programs": [[22, "format-for-electronic-delivery-of-report-and-programs"]], "Frequently used scaling functions": [[28, "frequently-used-scaling-functions"], [30, "frequently-used-scaling-functions"]], "From OLS to Ridge and Lasso": [[29, "from-ols-to-ridge-and-lasso"]], "From one to many layers, the universal approximation theorem": [[12, "from-one-to-many-layers-the-universal-approximation-theorem"]], "Functionality in Scikit-Learn": [[28, "functionality-in-scikit-learn"], [30, "functionality-in-scikit-learn"]], "Further Dimensionality Remarks": [[3, "further-dimensionality-remarks"]], "Further properties (important for our analyses later)": [[5, "further-properties-important-for-our-analyses-later"], [28, "further-properties-important-for-our-analyses-later"], [29, "further-properties-important-for-our-analyses-later"]], "Gaussian Elimination": [[21, "gaussian-elimination"]], "General Features": [[9, "general-features"]], "General linear models and linear algebra": [[27, "general-linear-models-and-linear-algebra"]], "Generalizing the fitting procedure as a linear algebra problem": [[27, "generalizing-the-fitting-procedure-as-a-linear-algebra-problem"], [27, "id1"]], "Generative Adversarial Networks": [[4, "generative-adversarial-networks"]], "Generative Models": [[4, "generative-models"]], "Generative Versus Discriminative Modeling": [[27, "generative-versus-discriminative-modeling"]], "Geometric Interpretation and link with Singular Value Decomposition": [[11, "geometric-interpretation-and-link-with-singular-value-decomposition"]], "Gradient Boosting, Classification Example": [[10, "gradient-boosting-classification-example"]], "Gradient Boosting, Examples of Regression": [[10, "gradient-boosting-examples-of-regression"]], "Gradient Clipping": [[1, "gradient-clipping"]], "Gradient Descent Example": [[29, "id1"], [30, "id1"]], "Gradient boosting: Basics with Steepest Descent/Functional Gradient Descent": [[10, "gradient-boosting-basics-with-steepest-descent-functional-gradient-descent"]], "Gradient descent": [[2, "gradient-descent"]], "Gradient descent and Ridge": [[29, "gradient-descent-and-ridge"], [30, "gradient-descent-and-ridge"]], "Gradient descent and revisiting Ordinary Least Squares from last week": [[30, "gradient-descent-and-revisiting-ordinary-least-squares-from-last-week"]], "Gradient descent example": [[29, "gradient-descent-example"], [30, "gradient-descent-example"]], "Grading": [[25, "grading"], [25, "id2"], [27, "grading"]], "How to take derivatives of Matrix-Vector expressions": [[16, "how-to-take-derivatives-of-matrix-vector-expressions"]], "Hyperplanes and all that": [[8, "hyperplanes-and-all-that"]], "Important Matrix and vector handling packages": [[21, "important-matrix-and-vector-handling-packages"]], "Important technicalities: More on Rescaling data": [[28, "important-technicalities-more-on-rescaling-data"]], "Improving gradient descent with momentum": [[30, "improving-gradient-descent-with-momentum"]], "Improving performance": [[1, "improving-performance"]], "In summary": [[25, "in-summary"]], "Including Stochastic Gradient Descent with Autograd": [[13, "including-stochastic-gradient-descent-with-autograd"], [30, "including-stochastic-gradient-descent-with-autograd"]], "Incremental PCA": [[11, "incremental-pca"]], "Installing R, C++, cython or Julia": [[27, "installing-r-c-cython-or-julia"]], "Installing R, C++, cython, Numba etc": [[27, "installing-r-c-cython-numba-etc"]], "Instructor information": [[25, "instructor-information"]], "Interpretations and optimizing our parameters": [[27, "interpretations-and-optimizing-our-parameters"], [27, "id2"], [27, "id3"], [28, "interpretations-and-optimizing-our-parameters"], [28, "id1"], [28, "id2"]], "Interpreting the Ridge results": [[28, "interpreting-the-ridge-results"], [29, "interpreting-the-ridge-results"], [29, "id4"]], "Introducing JAX": [[13, "introducing-jax"]], "Introducing the Covariance and Correlation functions": [[11, "introducing-the-covariance-and-correlation-functions"], [28, "introducing-the-covariance-and-correlation-functions"]], "Introduction": [[0, "introduction"], [6, "introduction"], [20, "introduction"], [21, "introduction"]], "Introduction to numerical projects": [[22, "introduction-to-numerical-projects"]], "Iterative Fitting, Classification and AdaBoost": [[10, "iterative-fitting-classification-and-adaboost"]], "Iterative Fitting, Regression and Squared-error Cost Function": [[10, "iterative-fitting-regression-and-squared-error-cost-function"]], "Kernel PCA": [[11, "kernel-pca"]], "Kernels and non-linearity": [[8, "kernels-and-non-linearity"]], "LU Decomposition, the inverse of a matrix": [[21, "lu-decomposition-the-inverse-of-a-matrix"]], "Lasso Regression": [[29, "lasso-regression"]], "Lasso case": [[29, "lasso-case"]], "Layers": [[1, "layers"]], "Layers used to build CNNs": [[3, "layers-used-to-build-cnns"]], "Learning goals": [[15, "learning-goals"], [16, "learning-goals"], [17, "learning-goals"], [18, "learning-goals"], [19, "learning-goals"]], "Learning outcomes": [[20, "learning-outcomes"], [27, "learning-outcomes"]], "Lectures and ComputerLab": [[27, "lectures-and-computerlab"]], "Limitations of supervised learning with deep networks": [[1, "limitations-of-supervised-learning-with-deep-networks"]], "Linear Algebra, Handling of Arrays and more Python Features": [[21, null]], "Linear Regression": [[0, null]], "Linear Regression Problems": [[28, "linear-regression-problems"], [29, "linear-regression-problems"]], "Linear Regression and the SVD": [[29, "linear-regression-and-the-svd"]], "Linear Regression, basic elements": [[0, "linear-regression-basic-elements"]], "Linking Bayes\u2019 Theorem with Ridge and Lasso Regression": [[5, "linking-bayes-theorem-with-ridge-and-lasso-regression"]], "Linking the regression analysis with a statistical interpretation": [[5, "linking-the-regression-analysis-with-a-statistical-interpretation"]], "Linking with the SVD": [[5, "linking-with-the-svd"], [28, "linking-with-the-svd"]], "Links to relevant courses at the University of Oslo": [[26, "links-to-relevant-courses-at-the-university-of-oslo"]], "Logistic Regression": [[7, null], [7, "id1"]], "MNIST and GANs": [[4, "mnist-and-gans"]], "Machine Learning": [[27, "machine-learning"]], "Machine learning": [[20, "machine-learning"]], "Main textbooks": [[27, "main-textbooks"]], "Making a tree": [[9, "making-a-tree"]], "Making your own Bootstrap: Changing the Level of the Decision Tree": [[10, "making-your-own-bootstrap-changing-the-level-of-the-decision-tree"]], "Making your own test-train splitting": [[28, "making-your-own-test-train-splitting"]], "Material for exercises week 35": [[28, "material-for-exercises-week-35"]], "Material for lab sessions sessions Tuesday and Wednesday": [[29, "material-for-lab-sessions-sessions-tuesday-and-wednesday"]], "Material for lecture Monday September 2": [[29, "material-for-lecture-monday-september-2"]], "Material for lecture Monday September 8": [[30, "material-for-lecture-monday-september-8"]], "Material for the lab sessions": [[30, "material-for-the-lab-sessions"]], "Mathematical Interpretation of Ordinary Least Squares": [[5, "mathematical-interpretation-of-ordinary-least-squares"], [28, "mathematical-interpretation-of-ordinary-least-squares"], [29, "mathematical-interpretation-of-ordinary-least-squares"]], "Mathematical optimization of convex functions": [[8, "mathematical-optimization-of-convex-functions"]], "Mathematics of CNNs": [[3, "mathematics-of-cnns"]], "Mathematics of the SVD and implications": [[5, "mathematics-of-the-svd-and-implications"], [28, "mathematics-of-the-svd-and-implications"], [29, "mathematics-of-the-svd-and-implications"]], "Matrices in Python": [[27, "matrices-in-python"]], "Matrix multiplication": [[1, "matrix-multiplication"]], "Matrix-vector notation and activation": [[12, "matrix-vector-notation-and-activation"]], "Meet the covariance!": [[24, "meet-the-covariance"]], "Meet the Covariance Matrix": [[5, "meet-the-covariance-matrix"], [28, "meet-the-covariance-matrix"]], "Meet the Hessian Matrix": [[28, "meet-the-hessian-matrix"]], "Meet the Pandas": [[27, "meet-the-pandas"]], "Min-Max Scaling": [[28, "min-max-scaling"]], "Momentum based GD": [[13, "momentum-based-gd"], [30, "momentum-based-gd"]], "More complicated Example: The Ising model": [[6, "more-complicated-example-the-ising-model"]], "More interpretations": [[28, "more-interpretations"], [29, "more-interpretations"], [29, "id5"]], "More on Dimensionalities": [[3, "more-on-dimensionalities"]], "More on Rescaling data": [[6, "more-on-rescaling-data"]], "More on Steepest descent": [[29, "more-on-steepest-descent"]], "More on convex functions": [[29, "more-on-convex-functions"]], "More preprocessing": [[28, "more-preprocessing"], [30, "more-preprocessing"]], "Motivation for Adaptive Step Sizes": [[30, "motivation-for-adaptive-step-sizes"]], "Multilayer perceptrons": [[12, "multilayer-perceptrons"]], "Network requirements": [[2, "network-requirements"]], "Neural Networks vs CNNs": [[3, "neural-networks-vs-cnns"]], "Neural networks": [[12, null]], "Note about SVD Calculations": [[28, "note-about-svd-calculations"], [29, "note-about-svd-calculations"]], "Note on Scikit-Learn": [[29, "note-on-scikit-learn"]], "Numerical experiments and the covariance, central limit theorem": [[24, "numerical-experiments-and-the-covariance-central-limit-theorem"]], "Numpy and arrays": [[21, "numpy-and-arrays"], [27, "numpy-and-arrays"]], "Numpy examples and Important Matrix and vector handling packages": [[27, "numpy-examples-and-important-matrix-and-vector-handling-packages"]], "Optimization and gradient descent, the central part of any Machine Learning algortithm": [[29, "optimization-and-gradient-descent-the-central-part-of-any-machine-learning-algortithm"]], "Optimization, the central part of any Machine Learning algortithm": [[13, null]], "Optimizing our parameters": [[27, "optimizing-our-parameters"]], "Optimizing our parameters, more details": [[27, "optimizing-our-parameters-more-details"]], "Optimizing the cost function": [[1, "optimizing-the-cost-function"]], "Organizing our data": [[0, "organizing-our-data"], [27, "organizing-our-data"]], "Other Matrix and Vector Operations": [[21, "other-matrix-and-vector-operations"]], "Other Types of Recurrent Neural Networks": [[4, "other-types-of-recurrent-neural-networks"]], "Other courses on Data science and Machine Learning at UiO": [[27, "other-courses-on-data-science-and-machine-learning-at-uio"]], "Other courses on Data science and Machine Learning at UiO, contn": [[27, "other-courses-on-data-science-and-machine-learning-at-uio-contn"]], "Other popular texts": [[27, "other-popular-texts"]], "Other techniques": [[11, "other-techniques"]], "Other types of networks": [[12, "other-types-of-networks"]], "Other ways of visualizing the trees": [[9, "other-ways-of-visualizing-the-trees"]], "Our model for the nuclear binding energies": [[27, "our-model-for-the-nuclear-binding-energies"]], "Overview of first week": [[27, "overview-of-first-week"]], "Overview video on Stochastic Gradient Descent (SGD)": [[30, "overview-video-on-stochastic-gradient-descent-sgd"]], "Own code for Ordinary Least Squares": [[27, "own-code-for-ordinary-least-squares"], [28, "own-code-for-ordinary-least-squares"]], "PCA and scikit-learn": [[11, "pca-and-scikit-learn"]], "Pandas AI": [[27, "pandas-ai"]], "Part a : Ordinary Least Square (OLS) for the Runge function": [[22, "part-a-ordinary-least-square-ols-for-the-runge-function"]], "Part b: Adding Ridge regression for the Runge function": [[22, "part-b-adding-ridge-regression-for-the-runge-function"]], "Part c: Writing your own gradient descent code": [[22, "part-c-writing-your-own-gradient-descent-code"]], "Part d: Including momentum and more advanced ways to update the learning the rate": [[22, "part-d-including-momentum-and-more-advanced-ways-to-update-the-learning-the-rate"]], "Part e: Writing our own code for Lasso regression": [[22, "part-e-writing-our-own-code-for-lasso-regression"]], "Part f: Stochastic gradient descent": [[22, "part-f-stochastic-gradient-descent"]], "Part g: Bias-variance trade-off and resampling techniques": [[22, "part-g-bias-variance-trade-off-and-resampling-techniques"]], "Part h): Cross-validation as resampling techniques, adding more complexity": [[22, "part-h-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Partial Differential Equations": [[2, "partial-differential-equations"]], "Plans for week 35": [[28, "plans-for-week-35"]], "Plans for week 36": [[29, "plans-for-week-36"]], "Plans for week 37, lecture Monday": [[30, "plans-for-week-37-lecture-monday"]], "Practical tips": [[13, "practical-tips"], [30, "practical-tips"]], "Practicalities": [[25, "practicalities"], [25, "id1"]], "Preamble: Note on writing reports, using reference material, AI and other tools": [[22, "preamble-note-on-writing-reports-using-reference-material-ai-and-other-tools"]], "Predicting New Points With A Trained Recurrent Neural Network": [[4, "predicting-new-points-with-a-trained-recurrent-neural-network"]], "Preprocessing our data": [[28, "preprocessing-our-data"]], "Prerequisites": [[27, "prerequisites"]], "Prerequisites and background": [[20, "prerequisites-and-background"]], "Prerequisites: Collect and pre-process data": [[3, "prerequisites-collect-and-pre-process-data"]], "Probability Distribution Functions": [[24, "probability-distribution-functions"]], "Program example for gradient descent with Ridge Regression": [[29, "program-example-for-gradient-descent-with-ridge-regression"], [30, "program-example-for-gradient-descent-with-ridge-regression"]], "Program for stochastic gradient": [[13, "program-for-stochastic-gradient"]], "Project 1 on Machine Learning, deadline October 6 (midnight), 2025": [[22, null]], "Properties of PDFs": [[24, "properties-of-pdfs"]], "Pros and cons": [[30, "pros-and-cons"]], "Pros and cons of trees, pros": [[9, "pros-and-cons-of-trees-pros"]], "Python installers": [[20, "python-installers"], [27, "python-installers"]], "RMS prop": [[13, "rms-prop"]], "RMSProp algorithm, taken from Goodfellow et al": [[30, "rmsprop-algorithm-taken-from-goodfellow-et-al"]], "RMSProp: Adaptive Learning Rates": [[30, "rmsprop-adaptive-learning-rates"]], "RMSprop for adaptive learning rate with Stochastic Gradient Descent": [[30, "rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent"]], "Random Numbers": [[24, "random-numbers"]], "Random forests": [[10, "random-forests"]], "Randomized PCA": [[11, "randomized-pca"]], "Reading material": [[27, "reading-material"]], "Reading recommendations:": [[28, "reading-recommendations"]], "Reading suggestions week 34": [[27, "reading-suggestions-week-34"]], "Readings and Videos:": [[30, "readings-and-videos"]], "Recurrent neural networks": [[12, "recurrent-neural-networks"]], "Recurrent neural networks: Overarching view": [[4, null]], "Reducing the number of degrees of freedom, overarching view": [[0, "reducing-the-number-of-degrees-of-freedom-overarching-view"], [28, "reducing-the-number-of-degrees-of-freedom-overarching-view"]], "Reformulating the problem": [[2, "reformulating-the-problem"]], "Regression Case": [[10, "regression-case"]], "Regression analysis and resampling methods": [[22, "regression-analysis-and-resampling-methods"]], "Regression analysis, overarching aims": [[27, "regression-analysis-overarching-aims"]], "Regression analysis, overarching aims II": [[27, "regression-analysis-overarching-aims-ii"]], "Regularization": [[1, "regularization"]], "Reminder from last week": [[28, "reminder-from-last-week"]], "Reminder on Newton-Raphson\u2019s method": [[29, "reminder-on-newton-raphson-s-method"]], "Reminder on Statistics": [[6, "reminder-on-statistics"]], "Reminder on different scaling methods": [[30, "reminder-on-different-scaling-methods"]], "Replace or not": [[13, "replace-or-not"], [30, "replace-or-not"]], "Required Technologies": [[20, "required-technologies"]], "Resampling Methods": [[6, null]], "Resampling and the Bias-Variance Trade-off": [[19, "resampling-and-the-bias-variance-trade-off"]], "Resampling methods": [[6, "id1"]], "Residual Error": [[28, "residual-error"], [29, "residual-error"]], "Resources on differential equations and deep learning": [[2, "resources-on-differential-equations-and-deep-learning"]], "Revisiting Ordinary Least Squares": [[29, "revisiting-ordinary-least-squares"]], "Revisiting our Linear Regression Solvers": [[13, "revisiting-our-linear-regression-solvers"]], "Rewriting the Covariance and/or Correlation Matrix": [[28, "rewriting-the-covariance-and-or-correlation-matrix"]], "Rewriting the fitting procedure as a linear algebra problem": [[27, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem"]], "Rewriting the fitting procedure as a linear algebra problem, more details": [[27, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem-more-details"]], "Ridge Regression": [[29, "ridge-regression"]], "Ridge and LASSO Regression": [[28, "ridge-and-lasso-regression"], [29, "ridge-and-lasso-regression"], [29, "id2"]], "Ridge and Lasso Regression": [[5, null], [5, "id1"]], "SGD example": [[30, "sgd-example"]], "SVD analysis": [[29, "svd-analysis"]], "Same code but now with momentum gradient descent": [[13, "same-code-but-now-with-momentum-gradient-descent"], [30, "same-code-but-now-with-momentum-gradient-descent"], [30, "id3"], [30, "id4"]], "Schedule first week": [[27, "schedule-first-week"]], "Schematic Regression Procedure": [[9, "schematic-regression-procedure"]], "Second moment of the gradient": [[30, "second-moment-of-the-gradient"]], "September 15-19": [[19, "september-15-19"]], "Setting up the Back propagation algorithm": [[12, "setting-up-the-back-propagation-algorithm"]], "Setting up the Matrix to be inverted": [[28, "setting-up-the-matrix-to-be-inverted"], [29, "setting-up-the-matrix-to-be-inverted"]], "Setting up the network using Autograd; The full program": [[2, "setting-up-the-network-using-autograd-the-full-program"]], "Similar (second order function now) problem but now with AdaGrad": [[13, "similar-second-order-function-now-problem-but-now-with-adagrad"], [30, "similar-second-order-function-now-problem-but-now-with-adagrad"]], "Simple Python Code to read in Data and perform Classification": [[9, "simple-python-code-to-read-in-data-and-perform-classification"]], "Simple case": [[28, "simple-case"], [29, "simple-case"]], "Simple code for solving the above problem": [[29, "simple-code-for-solving-the-above-problem"]], "Simple example code": [[30, "simple-example-code"]], "Simple example to illustrate Ordinary Least Squares, Ridge and Lasso Regression": [[29, "simple-example-to-illustrate-ordinary-least-squares-ridge-and-lasso-regression"]], "Simple geometric interpretation": [[29, "simple-geometric-interpretation"]], "Simple linear regression model using scikit-learn": [[0, "simple-linear-regression-model-using-scikit-learn"], [27, "simple-linear-regression-model-using-scikit-learn"]], "Simple one-dimensional second-order polynomial": [[18, "simple-one-dimensional-second-order-polynomial"]], "Simple program": [[29, "simple-program"], [30, "simple-program"]], "Slightly different approach": [[30, "slightly-different-approach"]], "Sneaking in automatic differentiation using Autograd": [[30, "sneaking-in-automatic-differentiation-using-autograd"]], "Software and needed installations": [[22, "software-and-needed-installations"], [27, "software-and-needed-installations"]], "Solving Differential Equations with Deep Learning": [[2, null]], "Solving the one dimensional Poisson equation": [[2, "solving-the-one-dimensional-poisson-equation"]], "Solving the wave equation with Neural Networks": [[2, "solving-the-wave-equation-with-neural-networks"]], "Some famous Matrices": [[21, "some-famous-matrices"]], "Some simple problems": [[13, "some-simple-problems"], [29, "some-simple-problems"]], "Some useful matrix and vector expressions": [[28, "some-useful-matrix-and-vector-expressions"]], "Splitting our Data in Training and Test data": [[0, "splitting-our-data-in-training-and-test-data"], [28, "splitting-our-data-in-training-and-test-data"]], "Standard steepest descent": [[13, "standard-steepest-descent"]], "Statistical analysis and optimization of data": [[20, "statistical-analysis-and-optimization-of-data"], [27, "statistical-analysis-and-optimization-of-data"]], "Steepest descent": [[13, "steepest-descent"], [29, "steepest-descent"]], "Stochastic Gradient Descent": [[30, "stochastic-gradient-descent"]], "Stochastic Gradient Descent (SGD)": [[13, "stochastic-gradient-descent-sgd"], [30, "stochastic-gradient-descent-sgd"]], "Stochastic variables and the main concepts, the discrete case": [[24, "stochastic-variables-and-the-main-concepts-the-discrete-case"]], "Support Vector Machines, overarching aims": [[8, null]], "Systematic reduction": [[3, "systematic-reduction"]], "Teachers": [[27, "teachers"]], "Teachers and Grading": [[25, null]], "Teaching Assistants Fall semester 2023": [[25, "teaching-assistants-fall-semester-2023"]], "Tentative deadllines for projects": [[25, "tentative-deadllines-for-projects"]], "Testing the Means Squared Error as function of Complexity": [[0, "testing-the-means-squared-error-as-function-of-complexity"], [28, "testing-the-means-squared-error-as-function-of-complexity"]], "Textbooks": [[26, null]], "The Algorithm before theorem": [[11, "the-algorithm-before-theorem"]], "The Breast Cancer Data, now with Keras": [[1, "the-breast-cancer-data-now-with-keras"]], "The CART algorithm for Classification": [[9, "the-cart-algorithm-for-classification"]], "The CART algorithm for Regression": [[9, "the-cart-algorithm-for-regression"]], "The CIFAR01 data set": [[3, "the-cifar01-data-set"]], "The Hessian matrix": [[29, "the-hessian-matrix"], [30, "the-hessian-matrix"]], "The Hessian matrix for Ridge Regression": [[29, "the-hessian-matrix-for-ridge-regression"], [30, "the-hessian-matrix-for-ridge-regression"]], "The Jacobian": [[28, "the-jacobian"]], "The MNIST dataset again": [[3, "the-mnist-dataset-again"]], "The OLS case": [[29, "the-ols-case"]], "The RELU function family": [[1, "the-relu-function-family"]], "The Ridge case": [[29, "the-ridge-case"]], "The SVD, a Fantastic Algorithm": [[28, "the-svd-a-fantastic-algorithm"], [29, "the-svd-a-fantastic-algorithm"]], "The Softmax function": [[1, "the-softmax-function"]], "The \\chi^2 function": [[0, "the-chi-2-function"], [27, "the-chi-2-function"], [27, "id4"], [27, "id5"], [27, "id6"], [27, "id7"], [27, "id8"]], "The bias-variance tradeoff": [[6, "the-bias-variance-tradeoff"]], "The code for solving the ODE": [[2, "the-code-for-solving-the-ode"]], "The complete code with a simple data set": [[28, "the-complete-code-with-a-simple-data-set"]], "The cost/loss function": [[28, "the-cost-loss-function"]], "The course has two central parts": [[20, "the-course-has-two-central-parts"]], "The derivative of the cost/loss function": [[29, "the-derivative-of-the-cost-loss-function"], [30, "the-derivative-of-the-cost-loss-function"]], "The equations": [[29, "the-equations"]], "The equations for ordinary least squares": [[28, "the-equations-for-ordinary-least-squares"]], "The first Case": [[29, "the-first-case"]], "The gradient step": [[30, "the-gradient-step"]], "The ideal": [[29, "the-ideal"]], "The logistic function": [[7, "the-logistic-function"]], "The mean squared error and its derivative": [[28, "the-mean-squared-error-and-its-derivative"]], "The moons example": [[8, "the-moons-example"]], "The multilayer perceptron (MLP)": [[12, "the-multilayer-perceptron-mlp"]], "The network with one input layer, specified number of hidden layers, and one output layer": [[2, "the-network-with-one-input-layer-specified-number-of-hidden-layers-and-one-output-layer"]], "The plethora of machine learning algorithms/methods": [[27, "the-plethora-of-machine-learning-algorithms-methods"]], "The sensitiveness of the gradient descent": [[29, "the-sensitiveness-of-the-gradient-descent"]], "The singular value decomposition": [[5, "the-singular-value-decomposition"], [28, "the-singular-value-decomposition"], [29, "the-singular-value-decomposition"]], "The two-dimensional case": [[8, "the-two-dimensional-case"]], "Time decay rate": [[30, "time-decay-rate"]], "To our real data: nuclear binding energies. Brief reminder on masses and binding energies": [[27, "to-our-real-data-nuclear-binding-energies-brief-reminder-on-masses-and-binding-energies"]], "Topics covered in this course: Statistical analysis and optimization of data": [[27, "topics-covered-in-this-course-statistical-analysis-and-optimization-of-data"]], "Towards the PCA theorem": [[11, "towards-the-pca-theorem"]], "Train and test datasets": [[1, "train-and-test-datasets"]], "Two-dimensional Objects": [[3, "two-dimensional-objects"]], "Type of problem": [[2, "type-of-problem"]], "Types of Machine Learning": [[27, "types-of-machine-learning"]], "Useful Python libraries": [[20, "useful-python-libraries"], [27, "useful-python-libraries"]], "Using Autograd": [[13, "using-autograd"]], "Using forward Euler to solve the ODE": [[2, "using-forward-euler-to-solve-the-ode"]], "Using gradient descent methods, limitations": [[13, "using-gradient-descent-methods-limitations"], [29, "using-gradient-descent-methods-limitations"], [30, "using-gradient-descent-methods-limitations"]], "Visualization": [[1, "visualization"], [1, "id1"]], "Visualizing the Tree, Classification": [[9, "visualizing-the-tree-classification"]], "Week 34: Introduction to the course, Logistics and Practicalities": [[27, null]], "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression": [[28, null]], "Week 36: Linear Regression and Gradient descent": [[29, null]], "Week 37: Gradient descent methods": [[30, null]], "What Is Generative Modeling?": [[27, "what-is-generative-modeling"]], "What does it mean?": [[28, "what-does-it-mean"], [29, "what-does-it-mean"]], "What is Machine Learning?": [[0, "what-is-machine-learning"]], "What is a good model?": [[0, "what-is-a-good-model"], [27, "what-is-a-good-model"]], "What is a good model? Can we define it?": [[27, "what-is-a-good-model-can-we-define-it"]], "When do we stop?": [[30, "when-do-we-stop"]], "Which activation function should I use?": [[1, "which-activation-function-should-i-use"]], "Why Combine Momentum and RMSProp?": [[30, "why-combine-momentum-and-rmsprop"]], "Why Linear Regression (aka Ordinary Least Squares and family)": [[27, "why-linear-regression-aka-ordinary-least-squares-and-family"]], "Wisconsin Cancer Data": [[7, "wisconsin-cancer-data"]], "With Lasso Regression": [[29, "with-lasso-regression"]], "Writing Our First Generative Adversarial Network": [[4, "writing-our-first-generative-adversarial-network"]], "Writing our own PCA code": [[11, "writing-our-own-pca-code"]], "Writing the Cost Function": [[29, "writing-the-cost-function"]], "XGBoost: Extreme Gradient Boosting": [[10, "xgboost-extreme-gradient-boosting"]], "Yet another Example": [[29, "yet-another-example"]], "a) Expression for Ridge regression": [[17, "a-expression-for-ridge-regression"]], "scikit-learn implementation": [[1, "scikit-learn-implementation"]]}, "docnames": ["chapter1", "chapter10", "chapter11", "chapter12", "chapter13", "chapter2", "chapter3", "chapter4", "chapter5", "chapter6", "chapter7", "chapter8", "chapter9", "chapteroptimization", "clustering", "exercisesweek34", "exercisesweek35", "exercisesweek36", "exercisesweek37", "exercisesweek38", "intro", "linalg", "project1", "schedule", "statistics", "teachers", "textbooks", "week34", "week35", "week36", "week37"], "envversion": {"sphinx": 62, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1}, "filenames": ["chapter1.ipynb", "chapter10.ipynb", "chapter11.ipynb", "chapter12.ipynb", "chapter13.ipynb", "chapter2.ipynb", "chapter3.ipynb", "chapter4.ipynb", "chapter5.ipynb", "chapter6.ipynb", "chapter7.ipynb", "chapter8.ipynb", "chapter9.ipynb", "chapteroptimization.ipynb", "clustering.ipynb", "exercisesweek34.ipynb", "exercisesweek35.ipynb", "exercisesweek36.ipynb", "exercisesweek37.ipynb", "exercisesweek38.ipynb", "intro.md", "linalg.ipynb", "project1.ipynb", "schedule.md", "statistics.ipynb", "teachers.md", "textbooks.md", "week34.ipynb", "week35.ipynb", "week36.ipynb", "week37.ipynb"], "indexentries": {}, "objects": {}, "objnames": {}, "objtypes": {}, "terms": {"": [0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 19, 20, 21, 22, 24, 25, 27, 28], "0": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 25, 27, 28, 29, 30], "00": [0, 1, 5, 11, 27, 28], "000": [1, 3], "00000000e": [], "001": [2, 8, 13, 29, 30], "004": 5, "004113634617443131": 28, "004113634617443139": 28, "00411363461744314": 28, "004113634617443147": 28, "00727646693": [0, 27], "0086649156": [0, 27], "01": [0, 1, 2, 5, 9, 11, 13, 17, 26, 27, 28, 30], "0110": 24, "01719003e": [], "02": [0, 4, 7, 12, 27], "02334824": [], "02857": 4, "02f": 6, "03077640549": 4, "03097597e": [], "031": 5, "04": 11, "0458": 9, "05": [4, 6], "062292565": 4, "062435": [], "06730814": [], "07": [], "0713": [0, 27], "07285": 3, "08": 24, "08078025e": [], "08336233266": 4, "08376632": 28, "083766322923899": 28, "0837663229239043": 28, "0917": 9, "0n": [0, 27], "0x113e21950": 17, "1": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 23, 24, 25, 26, 27, 29, 30], "10": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 23, 24, 25, 27, 28, 29, 30], "100": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 24, 25, 27, 28, 29, 30], "1000": [0, 1, 2, 4, 5, 8, 11, 13, 14, 18, 19, 20, 24, 27, 29, 30], "10000": [2, 5, 6, 10, 11, 13, 24], "100000": 8, "10001": 10, "1001": 24, "1002": 24, "1003": 24, "1005": 24, "1009": 24, "101": 16, "1011": 24, "1013": 24, "1013904243": 24, "1015": 24, "102": 16, "1023": 24, "1024": 3, "1026": 24, "1027": 24, "103": 1, "1030": 24, "1037": 24, "1038": 24, "1040": 24, "1047": 24, "107": 16, "108": [], "10th": 9, "10x": [0, 27], "11": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 21, 22, 24, 26, 27, 28, 29, 30], "110": [], "1100": 24, "1101": 24, "111": [1, 7, 12], "112": 16, "11340253": [], "11590451": [], "116": 16, "117": 16, "118": 16, "12": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 18, 21, 24, 26, 27, 28, 29, 30], "120": 3, "121": [8, 9, 10, 16], "1215pm": [25, 27], "122": [8, 9, 10], "124": [0, 27], "125": 16, "127": [4, 16], "128": [3, 4, 13, 30], "129": 16, "1298": 9, "12pm": [25, 27], "13": [0, 2, 9, 12, 21, 24, 27], "131": 16, "133": 7, "135": 16, "136": 16, "14": [0, 2, 4, 6, 8, 9, 10, 12, 21, 24, 26, 28], "141": 16, "1412": 30, "143": 16, "1446729567": 4, "149": 16, "14g": 6, "15": [0, 2, 4, 6, 7, 8, 9, 12, 13, 22, 24, 27, 29, 30], "150": [4, 8], "152": 16, "153760": [], "156": 16, "157": [], "158": [], "159": 16, "15g": 6, "15pm": 27, "16": [1, 2, 3, 4, 5, 8, 9, 10, 24, 27, 29], "160": 16, "1603": 3, "161": 16, "162": 16, "16231451": 4, "163": 16, "16384": 3, "164": 16, "167": 16, "17": [1, 2, 8, 24], "172": 16, "173": 16, "176": 16, "178": 16, "179": 16, "1797": 1, "18": [2, 6, 7, 8, 9, 10, 24, 27], "1807": 4, "18392847": [], "19": [2, 24, 27], "1940": [], "1943": 12, "19569961": 28, "1970": [21, 27], "1973": 9, "1979": 6, "1_1": 12, "1_2": 12, "1_3": 12, "1cm": [0, 8, 10, 24, 27], "1d": [1, 2, 3], "1e": [2, 4, 13, 14, 30], "1e10": 14, "1e4": 6, "1f": 1, "1k": 21, "1n": [0, 27], "1x": [0, 27], "2": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 24, 26, 30], "20": [0, 1, 2, 6, 7, 8, 16, 17, 24, 25, 27, 28, 29, 30], "200": [0, 2, 3, 4, 8, 9, 10], "2000": [0, 28], "2004": [13, 29], "2006": 26, "20072279": [], "2008": 27, "2010": 1, "2011": 1, "2012": 30, "2014": [4, 30], "2015": 1, "2016": [0, 27], "2018": [0, 6, 28], "2021": [6, 14, 28, 30], "2022": 27, "2025": [18, 27, 28, 29, 30], "21": [0, 1, 5, 7, 9, 12, 21, 27, 28, 29], "2116753732": 4, "215pm": [25, 27], "2167072": [], "22": [0, 1, 5, 12, 13, 21, 27, 28, 29], "221": 8, "225": 4, "22948497": [], "23": [1, 12, 21], "24": [0, 1, 21, 27], "25": [2, 3, 4, 5, 6, 8, 9, 11, 28], "250": [2, 4, 7, 9], "25000": [], "250154": [], "253775": [], "255": 3, "256": 4, "25x": 22, "26": [], "26303845": [], "264": [], "265": [], "265109911": 4, "266": [], "269": [], "27": 1, "270": [], "278": [29, 30], "27n_": 24, "28": [1, 3, 4], "283": [29, 30], "2830637392": 4, "2861": 24, "2873": 9, "2882": 24, "2886": 24, "2890": [0, 27], "2892": 24, "29": 28, "2915": 24, "2931": 27, "29364655": [], "294399745619595": [], "296247": [], "2968": 27, "2980": 27, "298273": [], "298375": [], "2990": 27, "2_": 12, "2_1": 12, "2_2": 12, "2_3": 12, "2_i": 12, "2_m": [6, 24], "2_t": 13, "2_x": 24, "2a": 17, "2b": 24, "2c8f433990d1": 30, "2cm": 8, "2d": [1, 3, 11, 12, 20, 27], "2e": 6, "2f": [0, 7, 9, 10, 11, 12, 27], "2g": 2, "2g_i": 2, "2k": 3, "2m": 6, "2mvizaqfst8": 28, "2n": [0, 2, 3, 27, 28], "2nd": 9, "2p": 24, "2pt": 4, "2x": [0, 3, 8, 13, 27], "2x_ix_jy_iy_j": 8, "2x_j": 8, "2y_i": 10, "2y_j": 8, "3": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 23, 24, 25, 27, 29, 30], "30": [0, 1, 4, 6, 7, 10, 13, 25, 30], "30000": [0, 27], "3072": 3, "31": [12, 21, 24], "315": [6, 28, 30], "3155": [0, 5, 6, 28, 29, 30], "32": [3, 4, 6, 12, 13, 21, 24, 30], "3200": 1, "3250": 1, "3297": [], "33": [12, 21, 25], "3303": [], "3310": [], "332331": [], "333": 7, "3331": [], "3337": [], "34": 21, "3436": [0, 27], "3437": [0, 27], "35": [0, 6, 22, 27, 29, 30], "3581341341": 4, "359": [5, 29], "36": [0, 5, 6, 18, 22, 24], "37": [22, 29], "370782966": 4, "38": [22, 24], "39": [0, 25, 27], "3d": [2, 3, 4, 6, 13, 16], "3f": [1, 3, 9], "3n": 21, "3x": [2, 8], "3x_i": 2, "3y": 8, "4": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 24, 27, 29, 30], "40": [1, 6, 25, 27], "400": 4, "4000": 27, "4050": [26, 27], "41": 21, "4155": [2, 15], "41589548": [], "42": [1, 4, 8, 9, 10, 21], "43": [0, 7, 21], "4310": 27, "436462435": 4, "44": [0, 21, 29, 30], "45": [25, 27], "46": [25, 27], "462": 7, "47": [25, 27], "479465113": 4, "47958494": [], "48": [], "48257387": [25, 27], "49": [5, 6, 11], "49152": 3, "4940954": [0, 27], "4990": 24, "4992": 24, "4997": 24, "4c4c7f": [9, 10], "4d": 3, "4f": 6, "4pm": [25, 27], "4y": 8, "4y_i": 10, "5": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 22, 24, 27, 28, 29, 30], "50": [1, 2, 3, 4, 6, 7, 8, 10, 13, 27, 28, 30], "500": [1, 3, 4, 6, 9, 10, 13, 30], "5018": 24, "506": [], "507d50": [9, 10], "50j": 13, "50x10": 1, "51": 10, "510": 1, "512132": [], "5177783846": 4, "53": 9, "54": [6, 24], "5411205": [], "54894451": [], "55": 1, "56": 1, "56536": [0, 27], "569": 1, "57": [0, 8, 25, 27], "571": [5, 29], "58": [10, 25, 27], "591317992": 4, "5cm": 24, "5f": [8, 30], "5x": [8, 18], "5y": 8, "6": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 18, 21, 24, 25, 27, 28, 29, 30], "60": [1, 3], "60000": 4, "6019067271": 4, "606439": [], "625": 7, "63": 1, "64": [1, 3, 4, 13, 21, 27, 30], "64x50": 1, "65": [1, 8, 9], "6887363571": 4, "69": [16, 24], "69069n_": 24, "691": [], "6980": 30, "6n_": 24, "7": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 21, 22, 24, 26, 27, 28, 30], "70": [1, 7], "70653767": 4, "71": 1, "724": 3, "73": [], "7304881": [], "75": [5, 6, 8, 11], "76": [25, 27], "765": 7, "77": [25, 27], "7718": 9, "7782028952": 4, "77893972": [], "78": [], "7d7d58": [9, 10], "8": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 21, 24, 25, 27, 29], "80": [0, 1, 5, 8, 17, 28], "800": [4, 7], "81": 1, "815am": [25, 27], "85": 1, "8702784034": 4, "88": 27, "8f": 6, "8g": 6, "8n": 21, "8x8": 1, "9": [0, 1, 2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 21, 24, 27, 30], "90": 1, "9040": 9, "91": [25, 27], "92": [25, 27], "93": 16, "931": [0, 27], "933": [5, 29], "937": 24, "938": 24, "939": [0, 24, 27], "94": 24, "95": [1, 11], "954": 24, "955820c21e8b": 4, "96": 6, "960": 24, "961": 24, "962": 24, "9649652536": 4, "96611194e": [], "9780387310732": 26, "9780387848570": 26, "9781098134174": 27, "9781492032632": 26, "9781801819312": 27, "97898392": 28, "98": [0, 1, 16], "985": 24, "986": 24, "989": 24, "9898ff": [9, 10], "99": [13, 16, 30], "991": 24, "992": 24, "993": 24, "996": 5, "999": [9, 24, 30], "9x": 6, "9y": 6, "A": [2, 3, 5, 6, 7, 10, 11, 12, 13, 15, 16, 19, 20, 21, 23, 24, 25, 26, 28, 29, 30], "AND": 2, "And": [0, 3, 4, 5, 6, 9, 13, 20, 22, 24, 29], "As": [0, 1, 2, 3, 4, 5, 6, 8, 10, 12, 13, 15, 16, 21, 22, 24, 27, 28, 29, 30], "At": [0, 4, 6, 13, 27, 30], "BE": [0, 27], "Be": [2, 18, 20, 27], "Being": 13, "But": [0, 1, 2, 3, 5, 6, 9, 10, 16, 24, 28], "By": [0, 3, 5, 6, 12, 13, 17, 21, 27, 28, 29, 30], "For": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30], "IF": [6, 28, 30], "IN": 26, "If": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 18, 20, 21, 22, 24, 27, 28, 29, 30], "In": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30], "Ising": [5, 12, 28, 29], "It": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 20, 21, 22, 24, 27, 28, 29, 30], "Its": [1, 2, 4, 11], "No": [6, 9, 27, 28, 30], "Not": [0, 1, 5, 6, 28, 29, 30], "OR": 24, "Of": 24, "On": [0, 3, 22, 24, 25, 26, 27], "One": [0, 1, 3, 4, 5, 6, 7, 8, 11, 12, 13, 17, 24, 28, 29, 30], "Or": [0, 1, 6, 27], "Such": [0, 6, 12, 16, 24, 30], "That": [0, 5, 7, 10, 11, 12, 14, 22, 24, 27], "The": [4, 10, 13, 14, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26], "Then": [0, 1, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 21, 27, 29, 30], "There": [0, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 21, 22, 24, 25, 27, 28, 29, 30], "These": [0, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 17, 18, 21, 22, 24, 25, 27, 28, 29, 30], "To": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 21, 24, 28, 29, 30], "With": [0, 5, 6, 8, 9, 10, 11, 12, 14, 16, 19, 21, 22, 24, 27, 28], "_": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 22, 27, 28, 29, 30], "_0": [5, 8, 10, 11, 13, 28, 29], "_1": [2, 5, 6, 8, 10, 11, 12, 13, 14, 21, 28, 29, 30], "_2": [2, 5, 8, 11, 12, 13, 21, 28, 30], "_3": 21, "_4": 21, "_9": [13, 30], "__class__": 10, "__doc__": 6, "__future__": [8, 9], "__init__": 1, "__main__": 2, "__name__": [2, 10], "_auto1": [2, 3, 4, 5, 6, 7, 12, 13, 21, 24, 28, 29], "_auto10": [6, 12], "_auto11": 6, "_auto12": 6, "_auto2": [2, 3, 4, 5, 6, 12, 13, 21, 24], "_auto3": [3, 4, 5, 6, 12, 13, 21], "_auto4": [4, 6, 12, 13, 21], "_auto5": [4, 6, 12, 13, 21], "_auto6": [4, 6, 12, 21], "_auto7": [4, 6, 12, 21], "_auto8": [6, 12], "_auto9": [6, 12], "_build": [0, 20, 22, 26, 27], "_c": 1, "_center": [], "_compon": 11, "_depth": 9, "_export": [15, 16], "_fraction": 9, "_i": [0, 1, 2, 5, 6, 7, 8, 11, 12, 13, 19, 22, 27, 28, 29, 30], "_j": [0, 1, 2, 3, 5, 6, 8, 13, 19, 22, 28, 29, 30], "_k": [13, 29, 30], "_l": 12, "_lambda": 6, "_leaf": 9, "_m": 10, "_multilayer_perceptron": [], "_n": [2, 5, 8, 11, 13, 28, 29, 30], "_node": 9, "_norm": [], "_p": [5, 8, 28, 29], "_ratio": 11, "_sampl": 9, "_split": [6, 9, 22], "_t": [13, 30], "_test": [6, 22], "_varianc": 11, "_weight": 9, "a0": 3, "a0faa0": [9, 10], "a1": [0, 27], "a2": [0, 27], "a3": [0, 27], "a4": [0, 27], "a_": [0, 1, 16, 21, 27, 28], "a_0": [0, 27], "a_1a": [0, 27], "a_2a": [0, 27], "a_3": [0, 27], "a_3a": [0, 27], "a_4": [0, 27], "a_4a": [0, 27], "a_h": 1, "a_i": [0, 1, 2, 12, 27], "a_j": [1, 12], "a_k": [0, 1, 12], "aaron": 26, "ab": [0, 2, 5, 13, 14, 27, 28, 30], "ab_channel": 20, "abandon": 1, "abid": 24, "abil": [0, 10], "abl": [0, 1, 4, 5, 6, 7, 10, 12, 13, 16, 18, 19, 22, 28, 29, 30], "about": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 25, 30], "abov": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 24, 26, 27, 28, 30], "abovement": [6, 22, 27], "abscissa": [13, 29], "absent": 30, "absolut": [0, 2, 5, 6, 13, 27, 28, 29], "absorb": [28, 29], "abstract": 1, "acceler": [13, 30], "accept": [0, 3, 6, 9, 22, 28], "access": [3, 11, 24, 27], "accid": [4, 6], "accompani": [0, 27, 28], "accomplish": [8, 9, 13, 30], "accord": [0, 1, 2, 5, 6, 9, 12, 13, 14, 24, 27, 29, 30], "accordingli": 11, "account": [0, 3, 5, 13, 15, 16, 24, 27], "accumul": [12, 13, 24, 30], "accur": [0, 3, 4, 6, 10, 13, 30], "accuraci": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 27, 28, 29], "accuracy_scor": [0, 1, 10, 27], "accuracy_score_numpi": 1, "achiev": [0, 1, 5, 6, 8, 12, 21, 27, 30], "aco": 24, "acquaint": 20, "acquir": [1, 20, 27], "acr": [], "across": [1, 3, 6, 9, 17, 20, 27], "act": [1, 3, 21], "action": 24, "activ": [0, 2, 3, 4, 9, 15, 23, 25, 27, 30], "actual": [0, 1, 4, 5, 6, 8, 11, 15, 16, 18, 21, 24, 27, 28, 29, 30], "ad": [1, 3, 4, 5, 8, 13, 15, 16, 21, 29, 30], "ada_clf": 10, "adaboostclassifi": 10, "adadelta": [13, 30], "adagrad": 22, "adam": [1, 3, 4, 22, 27], "adapt": [4, 6, 13, 17, 26, 29], "add": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 15, 16, 17, 18, 24, 25, 27, 28, 29, 30], "add_subplot": [1, 7, 12, 14], "addendum": 5, "addit": [0, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 15, 20, 21, 22, 24, 25, 26, 27, 28], "addition": [12, 13, 29, 30], "address": [1, 9, 11, 13, 27, 30], "adjac": [3, 12], "adjoint": [5, 28], "adjust": [0, 5, 12, 13, 29, 30], "admir": [0, 27], "advanc": [4, 6, 12, 26, 27, 30], "advantag": [1, 3, 5, 6, 10, 13, 21, 29, 30], "adversari": 27, "afecionado": 27, "affect": [3, 15], "affin": [0, 3, 8, 11, 28], "afford": 3, "aficionado": 27, "aforement": 14, "african": [], "after": [0, 1, 2, 4, 5, 6, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "afterward": [0, 27], "ag": [0, 7, 27, 28], "ag_0": 2, "again": [0, 1, 4, 5, 6, 7, 8, 10, 11, 12, 13, 22, 24, 27, 28, 29], "against": [1, 4, 7, 10], "agegroup": 7, "agegroupmean": 7, "aggreg": [9, 10], "agorithm": 10, "agre": [5, 6, 24, 28, 29, 30], "agreement": [13, 30], "ahead": 9, "ai": [0, 26], "aid": 11, "aim": [0, 1, 4, 6, 7, 11, 14, 16, 17, 19, 20, 21, 22, 28], "ainv": 5, "airplan": 3, "aka": 5, "al": [0, 2, 4, 16, 17, 26, 27, 28, 29], "alarm": [5, 7], "aldo": 28, "algebra": [0, 3, 5, 13, 20, 28, 29], "algorithm": [0, 1, 2, 4, 5, 6, 7, 8, 13, 14, 16, 20, 21, 22, 24, 26], "align": [0, 2, 5, 6, 7, 8, 13, 24, 27, 28, 29], "all": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30], "allevi": [1, 13, 29], "alloc": [3, 21], "allow": [0, 1, 2, 3, 5, 6, 8, 10, 13, 15, 20, 21, 22, 27, 28, 29, 30], "almost": [0, 1, 6, 8, 11, 13, 24, 29, 30], "alon": [2, 9, 30], "along": [2, 3, 4, 5, 6, 9, 10, 11, 15, 20, 21, 27, 28, 29], "alpha": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 14, 24, 27, 28, 29, 30], "alpha_": [10, 30], "alpha_0": 3, "alpha_1": 3, "alpha_2": 3, "alpha_i": [3, 13], "alpha_k": 13, "alpha_m": 10, "alpha_n": 3, "alpha_opt": 13, "alreadi": [2, 3, 4, 5, 6, 10, 12, 15, 20, 21, 24, 27, 28, 29], "also": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "alter": 1, "altern": [0, 1, 4, 5, 6, 8, 9, 11, 13, 15, 18, 21, 22, 27, 28, 30], "although": [0, 1, 5, 6, 8, 10, 13, 16, 27, 30], "alwai": [0, 3, 5, 6, 12, 13, 16, 22, 24, 27, 28, 29, 30], "am": 4, "ame2016": [0, 27], "american": [], "among": [0, 3, 5, 9, 10, 12, 21, 27, 28], "amongst": 5, "amount": [0, 1, 3, 4, 6, 8, 10, 14, 20], "an": [1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29, 30], "an_": 24, "anaconda": [0, 1, 20, 22, 27], "analogi": 13, "analys": 6, "analysi": [1, 3, 4, 7, 14, 19, 21, 26], "analyt": [2, 3, 5, 6, 7, 12, 13, 17, 20, 22, 27, 28, 29, 30], "analyz": [0, 1, 3, 4, 5, 6, 16, 22, 24, 28, 29], "andrew": 1, "angl": [0, 3, 9, 28, 30], "anharmon": 3, "ani": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 19, 24, 27, 28, 30], "anim": [4, 12], "ann": 12, "annot": [0, 1, 3, 7, 8, 27], "announc": 27, "anonym": 18, "anoth": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 21, 22, 24, 27, 28, 30], "ansatz": [0, 18, 27], "answer": [0, 1, 3, 5, 6, 21, 22, 25, 27], "antialias": [2, 6], "anticip": 4, "anymor": [1, 8], "anyon": [4, 8, 15], "anyth": [1, 15, 16, 24], "anytim": [25, 27], "apach": 1, "apart": [11, 13, 29], "api": [1, 20, 27], "appar": 2, "appear": [0, 1, 3, 13, 21, 24], "append": [1, 3, 4, 8, 9, 13, 19, 27, 30], "appendix": 22, "appli": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 18, 22, 24, 26, 27, 28, 30], "applic": [0, 1, 3, 4, 5, 6, 7, 9, 12, 13, 16, 21, 24, 26, 27, 28, 29, 30], "apply_gradi": 4, "approach": [1, 2, 4, 5, 6, 9, 10, 11, 12, 13, 15, 16, 18, 20, 22, 24, 26, 28, 29], "approch": 22, "appropri": [2, 6, 9, 12, 13, 17, 20, 24], "approv": 27, "approx": [0, 2, 3, 6, 10, 11, 13, 18, 22, 24, 27, 29, 30], "approxim": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11, 13, 19, 22, 24, 27, 28, 29, 30], "apt": [0, 20, 22, 27], "aq": 24, "ar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30], "aragorn": 27, "arang": [1, 3, 4, 6, 7, 9, 10, 12, 13, 27, 30], "arbitrari": [1, 4, 6, 8, 12, 13, 24, 29], "arbitrarili": [0, 1, 11, 27], "arc": 6, "architectur": [3, 4, 12], "archiv": 22, "area": [0, 3, 6, 26, 27], "argmax": [1, 11], "argmin": [4, 10, 14], "argsort": 11, "argu": [1, 13], "argument": [0, 2, 3, 5, 11, 12, 13, 17, 27, 28, 30], "aris": [0, 6, 12, 13, 24, 27, 29], "arithmet": [0, 13, 21, 27], "arm": [6, 28, 30], "armadillo": 21, "around": [0, 1, 4, 5, 6, 11, 18, 22, 24, 27], "arrai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 13, 14, 16, 18, 20, 22, 24, 28, 29, 30], "arrang": [3, 27], "arraybox": 13, "arriv": [0, 6, 9, 11, 21, 24, 27], "arrow": 12, "arrowprop": 8, "art": [0, 1, 20], "articl": [0, 3, 4, 6, 10, 19, 27, 28, 29, 30], "artifici": [0, 2, 7, 12, 26, 27], "artificialneuron": 12, "arug": 13, "arxiv": [3, 4, 30], "asarrai": [0, 6, 9, 28, 30], "asid": 28, "ask": [5, 6, 11, 12, 15, 22], "aspect": [0, 6, 20, 27, 28], "assembl": 3, "assembli": [0, 27], "assert": 4, "assess": [0, 6, 22, 27, 28], "assici": 4, "assign": [0, 7, 8, 9, 12, 13, 14, 15, 23, 25, 26, 27], "associ": [0, 6, 9, 12, 14, 24, 27], "assum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 21, 22, 24, 27, 28, 29, 30], "assumpt": [0, 3, 5, 6, 9, 11, 24, 27, 28], "ast": [0, 5, 6, 27], "astyp": [4, 9, 10], "asymmetri": [0, 27], "asymptot": [4, 6], "atom": [0, 27], "attempt": [0, 4, 6, 7, 8, 10, 27, 28, 30], "attend": 27, "attent": [0, 21, 27], "attract": [0, 10, 27], "attribut": [0, 9, 27], "audi": [0, 27], "audio": [3, 4], "august": [27, 28], "aurelien": [0, 26, 27], "austfjel": 6, "auth": 15, "authent": 15, "author": [0, 1, 10, 24], "authour": 27, "auto": [9, 10, 24], "auto_exampl": [22, 28], "autocor": 24, "autocorrelation_tim": 24, "autocorrelform": 24, "autocovari": 24, "autoencod": [4, 20, 27], "autoencond": 20, "autograd": [20, 27], "autom": [0, 20, 26, 27], "automac": 21, "automag": 27, "automat": [0, 1, 2, 3, 4, 11, 16, 20, 21, 27], "automobil": 3, "autonom": 4, "avail": [0, 1, 4, 6, 10, 11, 20, 21, 22, 23, 25, 26, 27], "averag": [0, 1, 3, 6, 9, 10, 13, 14, 24, 25, 27, 28], "avoid": [0, 4, 5, 6, 9, 11, 13, 18, 21, 28, 30], "awai": [2, 3, 6, 28, 30], "awar": [2, 10], "award": [25, 27], "ax": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 27], "axes3d": [2, 6, 13, 29, 30], "axes_grid1": 6, "axhlin": 8, "axi": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 21, 24, 27, 28, 29, 30], "axiom": 5, "axvlin": [4, 8], "axvspan": 4, "b": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 24, 25, 27, 28, 29, 30], "b1": 8, "b2": 8, "b3": 8, "b_": [0, 1, 21], "b_0": 0, "b_1": [0, 2, 12, 13, 30], "b_2": [0, 13], "b_5": [13, 30], "b_group": 9, "b_i": [0, 1, 2, 12, 27], "b_ia_": [0, 27], "b_ia_i": 0, "b_index": 9, "b_j": [1, 12], "b_k": [0, 1, 12, 13, 30], "b_m": 12, "b_score": 9, "b_valu": 9, "ba": 30, "babcock": 27, "bachelor": [23, 25], "back": [0, 3, 4, 5, 6, 8, 9, 10, 15, 16, 21, 24, 27, 30], "backbon": 21, "backend": [1, 4], "background": [26, 27], "backpropag": 1, "backtrack": 9, "backup": 21, "backward": [1, 2, 4, 12, 21], "bad": [6, 17, 28], "badli": 24, "bag": [9, 20, 27], "bag_clf": 10, "baggin": 27, "baggingboot": 10, "baggingclassifi": 10, "baggingtre": 10, "balanc": [6, 30], "ballpark": 18, "band": 21, "bandwidth": 21, "bar": [0, 6, 11, 22, 27], "barber": 26, "bare": [4, 10], "base": [0, 1, 3, 4, 5, 7, 8, 9, 10, 14, 15, 16, 17, 20, 24, 25, 26, 27, 28, 29], "basi": [5, 7, 8, 10, 11, 12, 13, 21, 28, 29], "basic": [6, 8, 12, 13, 14, 15, 20, 22, 24, 27], "batch": [3, 4, 11, 12, 13, 29], "batch_shap": 4, "batch_siz": [1, 3, 4], "batchnorm": 4, "bay": 7, "bayesian": [5, 20, 26, 27], "becaus": [0, 1, 2, 3, 4, 5, 6, 8, 9, 12, 13, 14, 27, 28, 29, 30], "becom": [0, 1, 2, 5, 6, 7, 9, 12, 13, 24, 27, 28, 29, 30], "been": [0, 1, 2, 3, 4, 5, 6, 11, 12, 13, 20, 21, 22, 27, 28, 30], "befor": [0, 1, 2, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 27, 28, 30], "beforehand": [0, 24, 27], "begin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 21, 24, 25, 27, 28, 29, 30], "behav": [1, 6, 13, 29], "behavior": [0, 1, 13, 27, 29, 30], "behaviour": [12, 30], "behind": [0, 1, 6, 8, 13, 27, 29], "being": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11, 12, 13, 17, 24, 27, 28, 29, 30], "believ": [9, 21], "belong": [7, 8, 9, 13, 14, 29], "below": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 18, 21, 22, 24, 27, 28, 29, 30], "benchmark": 10, "benefici": [1, 13], "benefit": [0, 1, 4, 11, 13, 20, 27, 29, 30], "bengio": [1, 26, 27, 28, 30], "benign": [1, 7], "besid": [4, 5, 29], "bessel": [5, 28], "best": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 18, 25, 27, 28, 29, 30], "beta": [1, 3, 10, 11, 13, 16, 17, 19, 27, 28, 29], "beta1": [], "beta2": [], "beta_": [3, 13, 17, 28], "beta_0": [1, 3, 13, 28], "beta_1": [1, 3, 10, 13, 28, 30], "beta_1m_": 30, "beta_1x_i": 13, "beta_2": [3, 13, 30], "beta_2v_": 30, "beta_3": 3, "beta_i": [3, 30], "beta_j": [13, 28], "beta_k": 13, "beta_linreg": 13, "beta_m": 10, "beta_mg_m": 10, "beta_n": 3, "better": [0, 1, 2, 3, 4, 6, 9, 10, 11, 12, 13, 27, 28, 30], "between": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 24, 27, 28, 29, 30], "beyond": [0, 1, 5, 6, 8, 13, 27, 28, 29, 30], "bf": [13, 14, 19, 21, 24, 29], "bg": 27, "bgd": [13, 30], "bia": [0, 1, 2, 3, 5, 8, 9, 10, 12, 13, 27, 28, 29], "bias": [1, 2, 3, 5, 6, 9, 12, 19, 30], "bibliographi": 22, "big": [0, 1, 2, 5, 6, 14, 19], "bigger": [1, 6, 28], "bigr": 12, "bike": 9, "bilbo": 27, "billion": [3, 12, 20], "bin": [7, 24], "binari": [0, 3, 5, 7, 9, 10, 12, 27], "binarycrossentropi": 4, "bind": 0, "binomi": [20, 24, 27], "binsboot": 6, "bioinformat": 0, "biolog": [1, 12], "bios1100": [20, 27], "bird": [0, 3], "birth": 27, "bishop": [26, 27], "bit": [1, 4, 21, 24, 27], "bitwis": 24, "bivari": 2, "bk": [13, 30], "bla": [21, 27], "black": [8, 9, 14], "block": [6, 10, 20, 21, 24, 27], "blog": 27, "blogpost": 4, "blue": [0, 3], "bm": [], "bmatrix": [0, 1, 3, 5, 7, 8, 11, 13, 21, 27, 28, 29, 30], "bmi": 1, "bodi": [0, 1, 4, 12], "bold": 1, "boldfac": [0, 5, 16, 28, 29], "boldsymbol": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 22, 27, 29, 30], "boltzmann": [12, 20, 27], "book": [17, 22, 26, 27, 28], "book1": 26, "boolean": [4, 17], "boost": [1, 9, 20, 27], "boostrap": 10, "bootstrap": [1, 13, 19, 20, 22, 27, 30], "borrow": 27, "boston_dataset": [], "bot": 8, "both": [0, 1, 4, 5, 6, 8, 9, 10, 13, 14, 15, 16, 17, 20, 21, 22, 24, 25, 27, 28, 29, 30], "bottl": 7, "bound": [8, 12, 30], "boundari": [2, 4, 8, 11, 12], "box": [4, 9], "boyd": [8, 13, 29], "bracket": [4, 24], "brain": [1, 7, 12], "branch": [9, 27], "break": [0, 4, 6, 11, 14, 27, 30], "breast": [5, 7, 11], "breviti": 13, "brew": [0, 20, 22, 27], "brg": 8, "brief": [22, 28], "briefli": [0, 16, 27], "bring": [0, 5, 6, 10, 28, 30], "britt": [25, 27], "broad": 0, "broadli": 27, "brought": [13, 20, 27], "brownle": 4, "browser": [15, 27], "brute": [3, 5, 11, 28], "buffer_s": 4, "bui": 4, "build": [0, 4, 5, 6, 10, 16, 21, 24, 27], "built": [1, 3, 4, 6], "bunch": 11, "busi": [], "byte": [21, 27], "c": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 23, 24, 25, 26, 28, 29, 30], "c1": [8, 11], "c2": [8, 11], "c_": [8, 9, 10, 13, 24, 29, 30], "c_0": 24, "c_1": 12, "c_2": 12, "c_3": 12, "c_4": 12, "c_i": [12, 13, 30], "c_k": 24, "ca": [1, 27], "cach": 10, "cal": [0, 8, 10, 12, 13, 29, 30], "calcul": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 19, 21, 24, 27, 30], "california": 22, "call": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "calor": [0, 28], "cambridg": [13, 26, 29], "can": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29], "cancel": [0, 13, 27, 28], "cancer": [5, 10], "cancerpd": 7, "candid": [8, 9, 10, 30], "cannot": [0, 1, 4, 5, 6, 7, 8, 9, 22, 24, 28, 29], "canopi": [0, 20, 22, 27], "canva": [15, 16, 22, 27], "cap": 5, "capabl": [0, 1, 8, 13, 20, 27], "capac": [2, 25], "capita": [], "caption": 22, "captur": [4, 11, 12, 27], "car": [3, 4], "card": [0, 7, 27], "cardin": 1, "care": [11, 15], "carefulli": [13, 30], "carlo": [0, 6, 20, 24, 26, 27], "carri": [2, 6, 7, 22], "cart": 10, "case": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 14, 15, 16, 20, 21, 22, 27, 30], "casella": 26, "cast": 1, "cat": [3, 4], "catch": 0, "categor": [0, 1, 3, 9, 11, 27], "categori": [0, 1, 3, 7, 10, 12, 14, 27], "categorical_crossentropi": [1, 3], "caus": [0, 5, 6, 24, 27, 28, 29, 30], "causal": 0, "causat": [0, 27], "cax": 1, "cb": [6, 27], "cbar": 1, "cc": [0, 1, 5, 13, 27, 28, 29], "ccc": [5, 12, 29], "cdf": 24, "cdot": [0, 2, 6, 12, 13, 14, 21, 24, 27, 29, 30], "celebr": [13, 29], "cell": 4, "center": [0, 1, 6, 7, 8, 9, 11, 14, 18, 22, 24, 27, 28, 30], "central": [0, 3, 5, 6, 8, 16, 21, 27, 28], "centroid": [14, 24], "centroid_differ": 14, "centuri": 3, "certain": [0, 3, 6, 7, 9, 24, 27, 28], "cg": 13, "cha": [], "chain": [0, 1, 13, 20, 24, 27], "challeng": 15, "chanc": [1, 5, 13, 24, 30], "chang": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 19, 21, 22, 24, 27, 28, 29, 30], "channel": 3, "chapter": [0, 6, 10, 11, 16, 17, 19, 21, 22, 26, 27, 28, 29, 30], "chapter3": [0, 22], "charact": [0, 3, 5, 27, 28, 29], "character": [8, 9, 10, 12, 24], "characterist": [0, 1, 3, 10, 13, 27], "charg": [0, 27], "charl": [], "chase": 4, "chatgpt": [15, 22], "chd": 7, "chddata": 7, "cheap": [5, 28, 29], "cheaper": [1, 13, 30], "check": [1, 3, 4, 5, 11, 13, 15, 16, 19, 21, 27, 30], "checkmark": 3, "checkpoint": 4, "checkpoint_dir": 4, "checkpoint_prefix": 4, "chen": 10, "cheng": 28, "chiaramont": 2, "childcar": 16, "children": 16, "choic": [0, 1, 2, 3, 4, 6, 9, 12, 13, 14, 21, 27, 28, 29, 30], "choleski": [5, 21, 28, 29], "choos": [2, 3, 6, 9, 10, 11, 13, 14, 15, 18, 19, 22, 29], "chosen": [0, 1, 2, 6, 8, 9, 10, 13, 16, 24, 27, 29, 30], "chosen_datapoint": 1, "christian": 26, "christoph": [26, 27], "cifar": 3, "cifar10": 3, "circ": [1, 12, 30], "circl": [0, 8, 12, 28, 30], "circuit": 3, "circumfer": 9, "circumv": [1, 5, 13, 28, 29, 30], "cite": 22, "ckpt": 4, "clariti": 24, "class": [0, 1, 3, 4, 6, 7, 8, 9, 11, 12, 13, 24, 27], "class_nam": [3, 9], "class_val": 9, "class_valu": 9, "classic": [7, 9, 13], "classif": [0, 3, 5, 6, 7, 8, 11, 12, 20, 22, 26, 27, 28], "classifi": [0, 1, 4, 7, 9, 10, 11, 27], "classificaton": 1, "classifii": 10, "clean": 1, "clear": [1, 5, 10, 12, 13, 30], "clearli": [0, 3, 5, 6, 7, 8, 24, 28, 29], "clever": [1, 10], "clf": [0, 6, 8, 9, 10, 27, 28], "clf3": 0, "clf_lasso": 6, "clf_ridg": 6, "cli": 15, "clip": [3, 24], "clone": [15, 25], "close": [0, 1, 2, 4, 6, 8, 9, 11, 12, 13, 14, 18, 24, 26, 27, 29, 30], "closer": [3, 5, 13, 28, 29], "closest": [8, 11, 13, 14], "closur": [20, 27], "cloud": [20, 27], "cluster": [0, 1, 4, 6, 11, 20, 27], "cluster_label": 14, "cm": [1, 2, 3, 6, 8, 13, 29, 30], "cmap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 27], "cmap_arg": 6, "cmd": [9, 15], "cn_": 24, "cnn": 12, "cnn_kera": 3, "cntk": [20, 27], "co": [0, 2, 3, 6, 9, 13, 27], "code": [0, 3, 4, 6, 7, 8, 18, 20, 21, 24, 26], "coef": [0, 27], "coef0": 8, "coef_": [0, 5, 6, 8, 9, 13, 16, 27, 28, 29, 30], "coeff": 5, "coeffici": [0, 3, 5, 6, 7, 8, 9, 13, 18, 21, 27, 28, 30], "coerc": [0, 6, 27], "coin": [10, 24], "coin_toss": 10, "col": [0, 11, 27, 28], "colab": [20, 27], "cold": 9, "colinear": [], "collabor": 22, "collaps": 8, "collect": [2, 6, 10, 11, 17, 20, 24, 26, 27], "collinear": [5, 28, 29], "color": [0, 3, 4, 6, 8, 9, 10, 24, 30], "color_channel": 3, "color_cod": 6, "colorbar": [1, 6], "colsample_bytre": 10, "colsaobject": 10, "column": [0, 1, 2, 5, 6, 7, 8, 9, 11, 12, 16, 17, 18, 21, 27, 28, 29, 30], "columntransform": 9, "com": [4, 6, 15, 16, 20, 22, 26, 27, 29, 30], "combin": [1, 2, 5, 6, 7, 10, 15, 18, 24], "come": [0, 1, 3, 4, 5, 12, 13, 14, 15, 27, 28, 29, 30], "command": [0, 1, 15], "comment": [0, 4, 5, 6, 22], "commerci": [0, 20, 22, 27], "commit": 15, "commod": [0, 27], "common": [0, 1, 3, 5, 6, 7, 9, 11, 13, 14, 16, 22, 24, 27, 28, 29, 30], "commonli": [0, 1, 4, 6, 7, 9, 13, 14, 28, 30], "commun": [0, 12, 15, 22], "commut": 3, "commutatitav": 3, "compact": [0, 1, 3, 5, 6, 7, 9, 11, 12, 13, 14, 27, 28], "compair": 0, "compar": [0, 3, 4, 5, 6, 11, 13, 18, 21, 22, 27, 28, 29, 30], "comparison": [2, 4, 13], "compat": 7, "compens": 30, "compet": 0, "competit": 10, "compil": [0, 1, 3, 4, 13, 20, 21, 27], "complet": [0, 2, 3, 4, 9, 12, 15, 16, 17, 18, 19, 27], "completenn": 12, "complex": [1, 5, 8, 9, 11, 12, 13, 16, 19, 27, 29], "complic": [0, 1, 9, 13, 22, 27, 29, 30], "compoment": 28, "compon": [0, 1, 3, 4, 5, 6, 7, 9, 14, 16, 20, 27, 28, 29], "components_": 11, "compos": [9, 12, 13, 14, 20, 27], "compphys": [0, 6, 16, 20, 22, 23, 25, 26, 27, 28, 29], "compress": [0, 27, 28], "compris": 6, "compromis": [5, 28, 29], "compulsori": [20, 27], "comput": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 18, 20, 21, 22, 23, 24, 26, 27, 28, 29], "computation": [0, 3, 6, 9, 13, 24, 27, 29, 30], "computationalscienceuio": 27, "computerlab": 22, "concaten": [2, 4, 6, 14], "concav": [1, 13, 28, 29], "concentr": 10, "concept": [0, 2, 20, 27, 28], "conceptu": [12, 13, 29], "concern": [0, 1, 4, 7, 27, 29], "concic": 27, "conclud": [0, 5, 13], "conclus": 1, "cond": 2, "conda": [0, 1, 20, 22, 27], "condis": 28, "condit": [0, 2, 4, 5, 6, 8, 9, 11, 13, 24, 27, 28, 30], "conduct": 20, "condwav": 2, "confid": [0, 5, 6, 7, 8, 19, 27, 28], "configur": 3, "confirm": [5, 12], "confus": [5, 6, 7, 10, 21, 28], "confusion_matrix": 9, "congruenti": 24, "conjug": [4, 8], "conjugaci": 13, "conjunct": 3, "connect": [0, 1, 3, 4, 9, 11, 12, 13, 21, 27, 28, 29], "consequ": [5, 6, 8, 10, 12, 13, 28, 29, 30], "conserv": [5, 14, 28, 29], "consid": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 16, 21, 22, 24, 27, 28, 29, 30], "consider": [0, 1, 5, 13, 27, 28, 29], "consist": [1, 2, 3, 4, 6, 12, 13, 22, 24, 28, 29], "constant": [0, 2, 4, 5, 6, 8, 12, 13, 16, 18, 24, 27, 28, 29, 30], "constitu": [0, 27], "constitut": [2, 6], "constrain": [1, 3, 5, 7, 11, 29], "constraint": [5, 6, 8, 13, 28, 29, 30], "construct": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 21, 24, 27, 28], "contact": [0, 27], "contain": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 18, 19, 21, 22, 24, 26, 27, 28, 29, 30], "contemporari": 27, "content": [1, 15, 20, 21, 27, 29, 30], "context": [6, 10, 13, 22, 29, 30], "contigu": 21, "contin": 19, "continu": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 19, 21, 22, 24, 27, 28, 29, 30], "contour": [9, 10, 13], "contourf": [8, 9, 10], "contrast": [1, 4, 9, 10, 12, 27, 30], "contribut": [0, 3, 5, 13, 18, 24, 27, 28, 29, 30], "contributor": [0, 22], "control": [0, 1, 3, 9, 13, 15, 20, 27], "conv": [3, 4], "conv2d": [3, 4], "conv2dtranspos": 4, "convei": 27, "conveni": [5, 6, 12, 13, 21, 22, 27, 29, 30], "convent": [12, 28], "converg": [1, 2, 4, 5, 8, 13, 14, 18, 28, 29], "convergencewarn": [], "convers": 30, "convert": [0, 1, 4, 5, 9, 11, 13, 21, 27, 28, 29], "converttomatrix": 4, "convex": [4, 5, 7, 28, 30], "convinc": [13, 29], "convolut": [1, 4, 20, 27], "cool": [4, 9], "coolwarm": 6, "coordin": [5, 12, 14, 28, 29, 30], "coorel": [], "copi": [0, 1, 14, 15, 28], "core": 10, "corel": 27, "coronari": 7, "corr": [5, 7, 11, 28], "correalt": [11, 20], "correct": [0, 1, 2, 3, 4, 5, 7, 13, 15, 21, 24, 27, 28, 29], "correctli": [1, 2, 6, 7, 10, 18, 19, 22], "correl": [0, 1, 3, 5, 6, 7, 10, 12, 13, 20, 24, 27, 29, 30], "correlation_matrix": [5, 7, 11, 28], "correspond": [0, 3, 5, 6, 8, 9, 11, 12, 20, 21, 22, 24, 27, 28, 29], "cortex": 12, "cosin": [3, 6], "cost": [0, 2, 3, 5, 6, 7, 8, 9, 12, 13, 16, 17, 18, 19, 22, 27], "cost_deep_grad": 2, "cost_funct": 2, "cost_function_deep": 2, "cost_function_deep_grad": 2, "cost_function_grad": 2, "cost_grad": 2, "cost_histori": [], "cost_ol": [], "cost_ridg": [], "cost_sum": 2, "costol": [13, 30], "could": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 21, 22, 24, 27, 28, 29, 30], "coulomb": [0, 27], "count": [0, 9, 15, 23, 24, 25, 27], "counteract": 30, "counterpart": 27, "countor": 13, "coupl": [4, 5, 6], "cours": [0, 1, 3, 5, 11, 15, 16, 17, 22, 25, 28], "coursework": 15, "courvil": [26, 27, 28, 30], "cov": [5, 6, 11, 21, 24, 27, 28], "cov_xi": [5, 11, 28], "cov_xx": [5, 11, 28], "cov_yi": [5, 11, 28], "covari": [0, 7, 20, 21, 27, 29], "covariance_matrix": [5, 11, 14], "cover": [0, 5, 20, 25, 26, 28, 29], "covert": [0, 27], "covxi": 24, "covxx": 24, "covxz": 24, "covyi": 24, "covyz": 24, "covzz": 24, "cpu": 1, "craft": 3, "creat": [1, 3, 4, 5, 9, 10, 11, 12, 15, 18, 19, 20, 27, 30], "create_biases_and_weight": 1, "create_convolutional_neural_network_kera": 3, "create_neural_network_kera": 1, "create_x": [5, 11], "credit": [0, 7, 25, 27], "crim": [], "crime": [], "criteria": [0, 4, 9, 10, 14, 24, 27], "criterion": [9, 10, 13, 18, 29, 30], "critic": [6, 22, 28], "critiqu": 22, "cross": [0, 1, 3, 7, 9, 10, 13, 15, 20, 24, 27, 28, 29, 30], "cross_entropi": 4, "cross_val_scor": 6, "cross_valid": [7, 10], "crossvalid": 6, "crucial": [1, 24, 30], "cs231": 3, "csr_matrix": [21, 27], "csv": [0, 4, 6, 7, 9], "ctnk": 1, "cubic": 0, "cumbersom": 5, "cumsum": [10, 11, 27], "cumul": [7, 10, 24, 30], "cumulative_heads_ratio": 10, "cup": 5, "current": [1, 2, 3, 4, 13, 14, 15, 16, 26, 29, 30], "curs": [0, 28], "curv": [6, 7, 10, 12, 22], "curvatur": [13, 29, 30], "custom": [6, 14], "custom_cmap": [9, 10], "custom_cmap2": [9, 10], "cutpoint": 9, "cv": [6, 7, 10], "cvxbook": [13, 29], "cvxopt": [5, 8, 28], "cycl": [1, 12], "d": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 21, 24, 25, 27, 28, 29, 30], "d2_g_t": 2, "d_f": [13, 29], "d_g_t": 2, "d_net_out": 2, "da": 3, "dagger": [5, 21, 28, 29], "dai": [1, 9, 20], "damp": 3, "darget": 9, "darkr": 24, "dat": [0, 27], "dat_id": [0, 6, 7, 9, 27], "data": [2, 4, 5, 8, 10, 12, 13, 14, 16, 19, 21, 22, 26, 29, 30], "data1": 14, "data2": 14, "data3": 14, "data4": 14, "data_id": [0, 6, 7, 9, 27], "data_indic": 1, "data_panda": 27, "data_path": [0, 6, 7, 9, 27], "databas": 1, "datafil": [0, 6, 7, 9, 27], "datafram": [0, 4, 5, 7, 9, 11, 27, 28], "datapoint": [1, 5, 6, 7, 11, 13, 16, 29, 30], "datasci": [15, 16], "dataset": [0, 4, 6, 7, 8, 9, 10, 11, 13, 14, 16, 22, 27, 29, 30], "datatyp": 4, "date": [15, 18, 22, 27, 28, 29, 30], "daughter": 10, "david": 26, "dbh": 1, "dbo": 1, "dcomposit": 21, "ddot": 2, "dead": 1, "deadlin": 15, "deal": [0, 1, 3, 5, 6, 8, 11, 13, 14, 19, 21, 24, 27, 28, 29, 30], "dealt": 0, "debt": 7, "debug": [0, 5, 6, 28, 29, 30], "decad": [0, 3, 30], "decai": [0, 13, 24, 27], "decemb": [25, 27], "decent": 10, "decid": [0, 2, 3, 5, 6, 9, 18, 28, 29, 30], "decim": [0, 27], "decis": [0, 1, 8, 11, 20, 26, 27], "decision_funct": 8, "decision_tre": 9, "decisiontreeclassifi": [9, 10], "decisiontreeregressor": [0, 9, 10], "declar": [0, 4, 21, 27], "decompos": [5, 6, 21, 28, 29], "decomposit": [0, 6, 12, 27], "decompost": [5, 28, 29], "deconvolut": 3, "decorrel": [10, 13, 30], "decreas": [1, 2, 4, 5, 6, 10, 11, 13, 19, 29, 30], "deduc": [0, 27], "deep": [3, 7, 12, 13, 20, 26, 28, 29, 30], "deep_neural_network": 2, "deep_param": 2, "deep_tree_clf": [9, 10], "deep_tree_clf1": 9, "deep_tree_clf2": 9, "deepen": [5, 20, 27], "deeper": [0, 3, 4, 27], "deeplearningbook": [26, 27, 29, 30], "deer": 3, "def": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 24, 27, 28, 29, 30], "def_covari": 24, "default": [0, 1, 2, 4, 6, 7, 21, 27, 28], "default_tim": 4, "defect": [5, 28, 29], "defici": [5, 28, 29], "defin": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 28, 29, 30], "definit": [1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 21, 24, 28, 29, 30], "defint": 24, "degre": [3, 5, 6, 8, 9, 10, 11, 15, 16, 19, 22, 24, 27, 29, 30], "deisenroth": 28, "del": 1, "delet": [6, 15], "delimit": 4, "deliv": [15, 23, 27], "delta": [0, 2, 3, 6, 8, 12, 13, 14, 27, 30], "delta_": [1, 21], "delta_0": 3, "delta_1": 3, "delta_2": 3, "delta_3": 3, "delta_4": 3, "delta_5": 3, "delta_h": [0, 1, 27], "delta_j": [3, 12], "delta_k": 12, "delta_l": [1, 3], "delta_momentum": [13, 30], "delta_n": [0, 3, 27], "delug": 20, "delv": 0, "demand": [13, 29], "demonstr": [0, 3, 5, 6, 7, 11, 12, 20, 27, 28, 29], "den": 4, "denomin": [1, 5, 30], "denot": [1, 2, 6, 7, 13, 24, 29, 30], "dens": [1, 3, 4], "densiti": [0, 2, 6, 24], "depart": [25, 27, 28, 29, 30], "depend": [0, 1, 2, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 29, 30], "depict": 24, "deploy": [0, 20, 22, 27], "depth": [0, 3, 9, 10, 21], "deriv": [0, 1, 2, 6, 7, 8, 10, 11, 13, 18, 20, 22, 27], "derivati": 13, "derivative_fn": 13, "descend": [5, 9, 11, 28, 29], "descent": [0, 1, 3, 7, 8, 12, 27, 28], "describ": [0, 2, 4, 5, 6, 8, 10, 11, 12, 13, 19, 21, 22, 27, 30], "descript": [0, 8, 9, 22, 27], "design": [0, 1, 3, 4, 5, 6, 7, 10, 11, 12, 13, 17, 18, 22, 27, 29, 30], "designmatrix": [0, 27], "desir": [0, 2, 4, 5, 13, 14, 27, 28, 29, 30], "desktop": 15, "despit": [1, 12], "destroi": 21, "det": [5, 21, 28, 29], "detail": [0, 6, 11, 13, 14, 18, 21, 22, 28, 29, 30], "detect": [3, 8, 12], "determin": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 18, 21, 24, 27, 28, 29, 30], "determinist": [7, 13, 24, 29, 30], "dev": [1, 22], "develop": [0, 3, 5, 8, 10, 11, 12, 20, 21, 22, 27, 28], "deviat": [0, 1, 2, 4, 5, 6, 17, 18, 19, 22, 24, 27, 28, 30], "devis": 12, "df": [4, 8, 11, 13, 27], "df1": 27, "di": [], "diag": [5, 8, 28, 29, 30], "diagnost": [1, 10], "diagon": [0, 5, 7, 13, 18, 19, 21, 24, 27, 28, 29, 30], "diagonaliz": [5, 28, 29], "diagram": 10, "diagsvd": 6, "dice": [6, 24], "dict": [6, 8], "dictionari": [], "did": [0, 1, 5, 6, 7, 10, 11, 14, 16, 22, 27], "die": 1, "diff": 2, "diff1": 2, "diff2": 2, "diff_ag": 2, "diffeent": 8, "differ": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29], "differenti": [0, 3, 16, 20, 21, 27, 28, 29], "difficult": [0, 1, 6, 10, 13, 24, 27, 30], "difficulti": [0, 1, 13, 27, 29], "diffonedim": 2, "digit": [0, 1, 3, 4, 6, 25, 27], "dilemma": [13, 30], "dilut": 1, "dim": [4, 11, 14, 21], "dimens": [0, 1, 2, 3, 4, 5, 8, 11, 14, 16, 21, 27, 28, 29], "dimension": [0, 4, 5, 6, 9, 11, 13, 14, 19, 20, 21, 22, 27, 28, 29, 30], "dimensionless": [0, 3, 27], "diment": 21, "diminish": 30, "dimnsion": 4, "diod": 3, "direct": [0, 1, 2, 4, 11, 12, 13, 14, 27, 28, 29, 30], "directli": [1, 4, 5, 6, 18, 24, 28, 29], "disadvantag": [0, 27, 30], "disappear": [3, 6], "disc_loss": 4, "disc_tap": 4, "discard": [6, 11], "disciplin": [0, 3, 12], "disclaim": 24, "discord": 27, "discourag": [13, 15, 29], "discov": [0, 27], "discover": 5, "discret": [1, 3, 5, 7, 13], "discrimin": [4, 7, 10, 11], "discriminator_loss": 4, "discriminator_loss_list": 4, "discriminator_model": 4, "discriminator_optim": 4, "discuss": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 30], "diseas": 7, "disguis": [6, 28, 30], "disord": [1, 7], "displai": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 22, 24, 27, 28], "displaystyl": [0, 5, 17, 27, 28, 29, 30], "disregard": [0, 27], "dissimilar": [11, 14], "dist": 14, "distanc": [8, 9, 11, 14, 24], "distance_list": 9, "distinct": [3, 7, 8, 9, 10, 14], "distinctli": 8, "distinguish": [0, 4, 7, 8, 24, 27], "distplot": [], "distribut": [0, 1, 4, 6, 7, 10, 11, 13, 14, 18, 19, 20, 21, 22, 27, 28, 29, 30], "distrubut": [0, 20, 22, 27], "dive": [0, 8, 21, 27], "diverg": [1, 13, 29, 30], "divid": [0, 1, 3, 5, 6, 7, 8, 9, 11, 12, 18, 24, 27, 28, 30], "divis": [6, 8, 9, 13, 18, 21, 24, 30], "dna": 7, "dnn": [0, 1, 2, 4, 12, 27], "dnn1": 4, "dnn2_gru2": 4, "dnn_kera": 1, "dnn_model": 1, "dnn_numpi": 1, "dnn_scikit": [0, 1, 27], "do": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 27, 28, 29], "doc": [0, 15, 16, 20, 22, 23, 25, 26, 27], "document": [4, 13, 15], "doe": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 17, 18, 21, 22, 24, 27, 30], "doesn": [3, 9, 12, 27], "dog": [1, 3, 4], "domain": [5, 8, 13, 22, 29], "domin": [0, 27], "don": [0, 1, 3, 5, 6, 8, 11, 13, 15, 16, 20, 22, 27, 28, 30], "done": [0, 2, 3, 4, 5, 6, 9, 10, 11, 13, 16, 21, 22, 27, 28, 29, 30], "dot": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 18, 21, 22, 24, 27, 28, 29, 30], "doubl": [3, 4, 16, 21, 27], "doubli": 1, "doubt": 22, "down": [0, 3, 6, 9, 11, 12, 13, 29, 30], "download": [0, 1, 3, 5, 6, 15, 21, 26, 27], "downsampl": 3, "dozen": 1, "dq": 6, "drag": 13, "dramat": 11, "drastic": 4, "draw": [4, 6, 10, 13, 29], "drawback": [0, 1, 3, 13, 28, 29, 30], "drawn": [1, 4, 6, 7, 11, 24, 27], "drive": [3, 4], "driven": 3, "drop": [0, 1, 5, 6, 11, 13, 24, 27, 28, 29], "dropna": [0, 6, 27], "dropout": 4, "dt": [2, 3, 13, 24], "dtype": [0, 1, 3, 4, 14, 21, 27], "dub": [0, 27], "due": [1, 2, 5, 6, 8, 10, 12, 13, 18, 25, 27, 28, 29, 30], "dummi": [], "dure": [0, 1, 3, 4, 8, 9, 11, 20, 22, 27, 30], "dwell": [], "dwh": 1, "dwo": 1, "dx": [2, 3, 8, 24], "dx_1": 24, "dx_1p": 6, "dx_2p": 6, "dx_mp": 6, "dx_n": 24, "dxp": 6, "dy": [1, 8, 24], "dynam": 4, "dz": 8, "e": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 24, 25, 27, 28, 29, 30], "e_": [0, 2, 27], "each": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 23, 24, 25, 27, 28, 29, 30], "eapprox": [0, 27], "earli": [1, 13, 30], "earlier": [0, 5, 7, 8, 9, 11, 12, 13, 27, 28], "earthexplor": 6, "eas": [6, 9, 14], "easi": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 20, 21, 27, 28, 29, 30], "easier": [5, 6, 8, 9, 13, 15, 22, 24, 27, 28, 29], "easiest": [13, 18], "easili": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 27, 28, 29, 30], "eastern": [25, 27], "ebind": [0, 27], "eblock": 9, "econometr": 27, "economi": 5, "ecosystem": [20, 27], "ect": 23, "edg": 3, "edgecolor": 6, "editor": 15, "edu": [13, 22, 29], "educ": [0, 22, 27], "eff": 24, "effect": [1, 4, 10, 13, 16, 17, 18, 24, 30], "effic": 1, "effici": [0, 3, 10, 13, 20, 21, 24, 27, 30], "efron": 6, "egrad": 13, "eig": [5, 11, 13, 21, 24, 27, 28, 29, 30], "eigen": 24, "eigenpair": [5, 11, 28, 29], "eigenvalu": [0, 5, 8, 11, 13, 21, 27, 28, 29, 30], "eigenvector": [5, 11, 13, 28, 29], "eight": [21, 27], "eigval": [21, 24, 27], "eigvalu": [11, 13, 29, 30], "eigvec": [21, 24, 27], "eigvector": [11, 13, 29, 30], "eir": [25, 27], "eispack": [21, 27], "either": [1, 5, 6, 7, 8, 9, 10, 11, 13, 18, 22, 24, 27, 28, 29, 30], "eivind": 25, "eivinsto": 25, "ekstr\u00f8m": 4, "elabor": 24, "elarn": 3, "electr": [0, 3, 12, 27], "electron": 27, "eleg": 11, "element": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 19, 20, 21, 22, 26, 28, 30], "elementari": [10, 13, 21], "elementwis": [3, 13], "elementwise_grad": [2, 13], "elessar": 27, "elif": 14, "elim": 21, "elimin": [3, 8], "elin": [25, 27], "ell_": [], "ellipsi": 16, "els": [1, 3, 4, 7, 9, 12, 13, 16, 21], "elu": 1, "elus": [0, 27], "email": [23, 25, 27], "embed": [0, 11, 28], "embodi": [6, 22], "emit": 24, "emner": 26, "emph": 30, "emphas": [0, 10, 20, 27], "emphasi": [0, 20, 26, 27], "empir": [1, 11, 24], "emploi": [0, 1, 5, 6, 11, 13, 24, 27, 28, 29], "employ": 0, "empti": [6, 10, 15], "emul": 12, "en": [20, 22, 26], "enabl": 11, "enbodi": 6, "encod": [0, 3, 5, 9, 11, 14, 27, 28, 29], "encompass": [0, 22, 24], "encount": [0, 1, 5, 7, 13, 15, 22, 24, 27, 28, 29], "encourag": [15, 22], "end": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 24, 25, 27, 28, 29, 30], "endpoint": [3, 6], "energi": [0, 4, 6], "enforc": 12, "eng": 26, "engin": [0, 1, 3, 4, 20, 27], "english": 22, "enocurag": 22, "enorm": 3, "enough": [0, 6, 13, 27, 29, 30], "ensembl": [1, 9, 27], "ensur": [0, 1, 2, 3, 5, 6, 11, 13, 18, 24, 28, 29, 30], "entail": 27, "enter": [5, 6, 28, 29, 30], "enthought": [0, 20, 22, 27], "entir": [1, 3, 7, 9, 20, 24, 27, 30], "entiti": [9, 12, 21, 27], "entri": [0, 5, 8, 11, 12, 21, 27, 28, 30], "entropi": [1, 3, 7, 10, 13, 27, 29, 30], "enumer": [0, 1, 2, 3, 4, 6, 8, 27, 28, 30], "env": 24, "environ": [2, 20, 22, 27], "environemnt": 15, "eo": [0, 6], "eol": 0, "eosfit": 0, "epoch": [0, 1, 3, 4, 12, 13, 27, 30], "epsilon": [0, 5, 6, 7, 13, 22, 27, 28, 29, 30], "epsilon_": [0, 27], "epsilon_0": [0, 27], "epsilon_1": [0, 27], "epsilon_2": [0, 27], "epsilon_i": [0, 27, 28], "eq": [3, 13, 14, 21, 24, 29], "eqnarrai": [3, 5, 6], "equal": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 16, 18, 21, 22, 24, 27, 28, 29, 30], "equat": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 17, 19, 21, 24, 27, 30], "equilibrium": [2, 12], "equiv": [3, 13, 21, 24, 29, 30], "equival": [0, 1, 5, 7, 8, 11, 13, 20, 21, 27, 28, 29, 30], "erf": 24, "eriador": 27, "err": [0, 10], "err_": 6, "err_sqr": 2, "errat": [13, 29, 30], "erron": 2, "error": [1, 2, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 24, 30], "error_estimate_corr_tim": 24, "error_hidden": 1, "error_output": 1, "escap": [13, 29, 30], "especi": [1, 3, 9, 12, 13, 15, 18, 22, 30], "essenti": [0, 5, 6, 9, 10, 12, 14, 15, 22, 24, 28, 29], "establish": [0, 6, 10, 11, 16, 22], "estim": [0, 1, 5, 6, 7, 10, 11, 13, 19, 20, 24, 27, 28, 29, 30], "estimated_mse_fold": 6, "estimated_mse_kfold": 6, "estimated_mse_sklearn": 6, "et": [0, 2, 4, 16, 17, 26, 27, 28, 29], "eta": [0, 1, 3, 8, 12, 13, 18, 27, 29, 30], "eta0": [8, 13], "eta_": 13, "eta_j": 30, "eta_t": [13, 30], "eta_v": [0, 1, 3, 27], "etc": [0, 1, 3, 5, 7, 8, 9, 11, 12, 13, 14, 20, 21, 22, 24, 28, 29, 30], "ethic": 20, "euclidean": [0, 14, 28, 30], "evalu": [0, 2, 3, 4, 5, 6, 9, 13, 15, 16, 17, 19, 22, 24, 27, 28, 29, 30], "evalut": [13, 22], "even": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 20, 21, 24, 27, 28, 29, 30], "evenli": 4, "event": [5, 7, 10, 24], "eventu": [0, 5, 6, 11, 12, 13, 22, 25, 28, 29, 30], "everi": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 14, 15, 20, 24, 25, 27, 28, 29, 30], "everyth": [4, 12, 16, 18], "everywher": [4, 13, 29], "evolv": 0, "exact": [0, 5, 11, 12, 13, 21, 24, 27, 28], "exactli": [0, 3, 4, 6, 12, 18, 20, 28, 30], "exam": 27, "examin": 6, "exampl": [0, 5, 11, 12, 13, 15, 16, 18, 20, 21, 22, 24, 26], "exce": [1, 12, 13, 30], "excel": [0, 1, 4, 5, 10, 22, 27, 28], "except": [3, 4, 6, 8, 9, 21], "excess": [0, 27], "excit": 0, "exclud": [1, 6, 12, 28, 30], "exclus": [0, 1, 3, 6, 24, 27], "execut": [2, 5, 13, 15, 28, 29], "exemplifi": [13, 30], "exercic": [25, 27], "exercis": [5, 20, 22, 23, 25, 27, 29, 30], "exhaust": 6, "exhibit": [0, 5, 6, 8, 27, 28], "exist": [0, 1, 2, 3, 5, 6, 7, 8, 9, 13, 19, 21, 22, 27, 29], "exit": [5, 21, 28, 29], "exp": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 16, 17, 19, 24, 28, 29, 30], "exp_term": 1, "expand": [5, 7, 11, 13, 29], "expans": [0, 3, 5, 8, 10, 12, 13, 27, 28, 29], "expect": [0, 1, 5, 6, 7, 11, 12, 13, 15, 18, 20, 22, 27, 28, 30], "expectation_value_of_h_wrt_p": 24, "expens": [6, 10, 13, 16, 29, 30], "experi": [0, 1, 6, 8, 13, 15, 20, 22, 27, 28, 29], "experiment": [0, 4, 6, 9, 24, 27], "expert": [1, 9], "explain": [0, 6, 9, 10, 11, 13, 16, 19, 22, 27, 29], "explained_variance_ratio_": 11, "explanatori": [0, 27], "explicit": [0, 3, 6, 13, 21, 22, 27, 28, 29, 30], "explicitli": [0, 4], "explod": 1, "exploit": [0, 3, 12, 13, 27], "explor": [1, 4, 6, 8, 13, 18, 20, 22, 27, 29, 30], "expon": 1, "exponenti": [0, 1, 5, 6, 10, 13, 24, 27, 29], "export": [9, 15, 16], "export_graphviz": 9, "export_text": 9, "exporttext": 9, "expos": 20, "express": [0, 2, 3, 5, 6, 7, 10, 12, 13, 18, 21, 22, 24, 27, 29, 30], "exptmean": 24, "exptvari": 24, "extend": [0, 2, 7, 11, 13, 20, 27, 30], "extens": [0, 12, 15, 20, 27], "extent": [0, 1, 6, 26], "extern": [3, 6, 9], "extra": [1, 3, 5, 15, 25, 27, 28, 29], "extract": [0, 3, 5, 6, 7, 8, 11, 13, 16, 17, 21, 27, 28], "extrapol": [0, 27], "extrem": [0, 1, 4, 5, 6, 7, 8, 9, 13, 15, 16, 21, 28, 29, 30], "extremum": [13, 29], "extrins": 11, "ey": [0, 5, 6, 13, 14, 18, 21, 27, 28, 29, 30], "f": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18, 19, 21, 24, 25, 27, 28, 29, 30], "f1": 13, "f11": [0, 27], "f12": [0, 27], "f13": [0, 27], "f1_grad": 13, "f1d": 13, "f2": 13, "f2_grad_x1": 13, "f2_grad_x1_analyt": 13, "f2_grad_x2": 13, "f2_grad_x2_analyt": 13, "f3": 13, "f3_grad": 13, "f3_grad_analyt": 13, "f4": 13, "f4_grad": 13, "f4_grad_analyt": 13, "f5": 13, "f5_grad": 13, "f6": 13, "f6_for": 13, "f6_for_grad": 13, "f6_grad_analyt": 13, "f6_while": 13, "f6_while_grad": 13, "f7": 13, "f7_grad": 13, "f7_grad_analyt": 13, "f8": 13, "f8_grad": 13, "f9": [0, 13, 27], "f9_altern": 13, "f9_alternative_grad": 13, "f9_grad": 13, "f_": 10, "f_0": [3, 10], "f_1": [10, 13, 29], "f_2": [12, 13, 29], "f_3": 12, "f_d": 24, "f_grad": 13, "f_grad_analyt": 13, "f_i": [0, 6, 12, 16], "f_m": [3, 10], "f_n": 3, "f_vec": 2, "face": [13, 27, 29], "facecolor": [6, 8, 24], "facil": [0, 20], "facilit": 12, "fact": [0, 1, 3, 5, 9, 11, 12, 13, 27, 28, 29], "factor": [0, 1, 3, 5, 6, 9, 10, 11, 13, 21, 24, 27, 28, 29], "factori": 13, "fade": 6, "fafab0": [9, 10], "fail": [0, 6, 13, 25, 27, 29], "failur": 7, "fairli": [1, 2, 18, 24, 30], "faisal": [16, 28], "fake": 4, "fake_loss": 4, "fake_output": 4, "fall": [8, 9, 23], "fals": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 14, 16, 17, 21, 27, 28, 29, 30], "famili": [0, 7, 8, 24, 28, 30], "familiar": [0, 3, 5, 6, 8, 15, 20, 21, 22, 24, 27], "famou": [6, 12], "far": [0, 3, 4, 5, 6, 8, 11, 12, 13, 14, 16, 27, 28, 29], "fashion": [0, 9, 10, 27], "fast": [1, 3, 6, 10, 12, 13, 20, 24, 27, 29, 30], "faster": [1, 11, 13, 30], "fastest": [13, 21, 29], "favor": 7, "favorit": 24, "fc": 3, "featur": [0, 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 15, 17, 18, 19, 20, 24, 27, 29, 30], "feature_nam": [1, 7, 9], "feautur": 9, "fed": 1, "feed": [0, 2, 3, 11, 20, 27], "feed_forward": 1, "feed_forward_out": 1, "feed_forward_train": 1, "feedback": [4, 27], "feeddorward": 4, "feedforward": [1, 4, 12], "feel": [0, 5, 6, 11, 13, 15, 16, 18, 20, 22, 25, 27], "feet": [], "felt": 22, "fetch": [6, 15], "few": [1, 3, 4, 5, 9, 17, 18, 24, 27], "fewer": [0, 9, 11, 27], "ffnn": [1, 12], "field": [0, 3, 6, 12, 20], "fifth": [0, 6, 27], "fig": [0, 1, 2, 3, 4, 6, 7, 12, 13, 14, 22, 27], "fig_id": [0, 6, 7, 9, 27], "figaxi": 24, "figsiz": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 27], "figur": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 20, 22, 27, 28, 29, 30], "figure_id": [0, 6, 7, 9, 27], "figurefil": [0, 6, 7, 9, 27], "file": [0, 4, 5, 6, 7, 9, 15, 22, 27], "file_prefix": 4, "filenam": 27, "fill": [5, 9, 18, 28, 29], "filter": [3, 4], "final": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 22, 23, 24, 25, 27, 29], "financ": 0, "find": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 22, 24, 27, 28, 29, 30], "fine": [0, 14], "finish": 2, "finit": [3, 5, 6, 12, 13, 17, 24, 28, 29], "finnicki": 15, "first": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 21, 22, 24, 25, 26, 28, 30], "first_moment": 30, "first_term": 30, "firsteigvector": 11, "fit": [1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 17, 18, 19, 22, 24, 28, 30], "fit_beta": 28, "fit_intercept": [0, 5, 6, 16, 28, 29, 30], "fit_mod": 9, "fit_theta": [6, 30], "fit_transform": [0, 6, 8, 9, 11, 15, 19], "fiti": [0, 27], "five": [0, 9, 27, 28], "fix": [0, 3, 4, 6, 10, 11, 12, 13, 22, 27], "flag": 4, "flat": [12, 13, 29, 30], "flatten": [1, 3, 4, 5, 21], "flexibl": [1, 6, 8, 10, 12, 27, 30], "flip": [25, 27], "float": [0, 3, 4, 5, 9, 11, 13, 14, 21, 27, 28, 29], "float32": [4, 9], "float64": [4, 21, 27], "flop": [5, 21, 28, 29], "flow": [1, 4, 12], "fluctuat": 5, "fly": 11, "fm": 0, "fmax": 3, "fmesh": 13, "fn": 7, "focu": [0, 3, 4, 5, 6, 15, 20, 22, 26, 27, 28, 29, 30], "focus": [1, 6, 7, 21, 28, 30], "fold": [6, 9, 22], "folder": [0, 4, 6, 15, 22, 27], "follow": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30], "font": [7, 24, 27], "fontdict": 24, "fontsiz": [1, 6, 8, 9, 10, 24], "fontweight": 1, "footprint": 3, "foral": [8, 28], "forc": [0, 5, 6, 10, 11, 28, 29, 30], "forcast": 4, "forecast": [4, 12], "forest": [0, 1, 9, 20, 27], "forget": [11, 30], "form": [0, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 29, 30], "formal": [3, 4, 14, 18, 24], "format": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 20, 24, 26], "format_data": 4, "formatstrformatt": [6, 13, 29, 30], "formul": [4, 6, 11, 14], "formula": [3, 13, 24, 29], "forth": [4, 12], "fortran": [0, 20, 21, 27], "fortran2003": [20, 27], "fortran2008": 22, "fortran90": 24, "fortun": [0, 11, 28], "forward": [0, 3, 6, 20, 21, 27], "found": [1, 2, 4, 5, 6, 12, 13, 19, 22, 27, 28, 30], "foundat": [20, 27], "four": [4, 5, 6, 8, 12, 21, 23, 25, 27, 29], "fourier": [0, 27], "fourierdef1": 3, "fourierdef2": 3, "fourierseriessign": 3, "fourth": [12, 27, 28], "fp": 7, "frac": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "fraction": 9, "frame": 7, "framework": [1, 8, 10, 24], "frank": [5, 11], "frankefunct": [5, 6, 11], "fredli": [25, 27], "free": [0, 6, 11, 13, 15, 16, 18, 20, 21, 22, 24, 25, 26, 27], "freecodecamp": 20, "freedom": [5, 29], "freeli": [0, 22], "freez": 15, "frequenc": [3, 6, 7, 24], "frequent": [0, 8, 9, 13, 29], "frequentist": 20, "fresh": 10, "fridai": [15, 25, 27], "friedman": [6, 19, 22, 26, 27], "friendli": 4, "fro": 22, "frodo": 27, "frog": 3, "from": [0, 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26], "from_cod": 9, "from_logit": [3, 4], "from_tensor_slic": 4, "front": [0, 4, 5, 27, 28, 29], "frustrat": 15, "fulfil": [2, 5, 12, 28, 29], "full": [1, 3, 5, 7, 9, 10, 13, 24, 27, 28, 29, 30], "full_matric": [5, 28, 29], "fulli": [3, 6, 12, 24], "fun": [20, 27], "func": 2, "function": [2, 3, 4, 5, 9, 14, 15, 16, 17, 18, 19, 20, 21], "functionali": 11, "fundament": [0, 6, 20, 27], "funtion": 2, "further": [2, 7, 9, 19, 27], "furthermor": [0, 3, 5, 6, 7, 11, 12, 13, 20, 22, 27, 28, 29, 30], "futur": [0, 4, 8, 9, 27], "fy": [15, 22, 23, 25, 26, 27], "fys4155": 22, "fys5419": [26, 27], "fys5429": [26, 27], "f\u00f8470": [25, 27], "g": [0, 1, 2, 3, 4, 6, 8, 9, 10, 11, 13, 15, 18, 24, 27, 28, 29, 30], "g0": 2, "g_": [2, 9, 10, 30], "g_0": 2, "g_1": [2, 10], "g_2": [2, 10], "g_analyt": 2, "g_dnn_ag": 2, "g_euler": 2, "g_i": 2, "g_m": [3, 10], "g_n": 3, "g_re": 2, "g_t": [2, 30], "g_t_d2t": 2, "g_t_d2x": 2, "g_t_dt": 2, "g_t_hessian": 2, "g_t_hessian_func": 2, "g_t_jacobian": 2, "g_t_jacobian_func": 2, "g_trial": 2, "g_trial_deep": 2, "g_vec": 2, "gain": [1, 5, 7, 9, 10, 13, 28, 29], "galleri": [0, 27], "game": 4, "gamge": 27, "gamma": [0, 2, 8, 9, 10, 11, 13, 27, 29], "gamma1": 8, "gamma2": 8, "gamma_": [0, 27], "gamma_0": 10, "gamma_1": 10, "gamma_1x": 10, "gamma_i": [0, 8, 24, 27], "gamma_j": 13, "gamma_k": [13, 29], "gamma_m": 10, "gamma_x": [0, 27], "gap": 8, "gate": [4, 12], "gather": [0, 1, 12, 28], "gaug": 12, "gaussbacksub": 21, "gaussian": [4, 5, 6, 8, 14, 18, 24, 27], "gaussian_point": 14, "gaussian_rbf": 8, "gave": [13, 30], "gavra": 27, "gbc": 27, "gca": [2, 6, 8, 13], "gd": [1, 29], "gd_clf": 10, "gdclassiffiercgain": 10, "gdclassiffierconfus": 10, "gdclassiffierroc": 10, "gdm": 13, "gdregress": 10, "ge": [1, 5, 7, 24, 28, 29], "gen_loss": 4, "gen_tap": 4, "gender": [0, 27], "genener": 4, "gener": [0, 1, 2, 3, 5, 6, 8, 10, 11, 12, 13, 14, 15, 16, 18, 21, 22, 24, 26, 28, 29, 30], "generaliz": 16, "generallay": 12, "generate_and_save_imag": 4, "generate_imag": 4, "generate_latent_point": 4, "generate_simple_clustering_dataset": 14, "generated_imag": 4, "generator_loss": 4, "generator_loss_list": 4, "generator_model": 4, "generator_optim": 4, "genom": 20, "geodes": 11, "geoff": 30, "geometr": [0, 13, 27], "geometri": 5, "georg": 26, "geotif": 6, "geq": [2, 5, 8, 9, 13, 28, 29, 30], "geron": [0, 26, 27], "get": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 15, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "get_dummi": 9, "get_paramet": 2, "get_split": 9, "get_yaxi": 8, "get_yticklabel": 6, "gh": 15, "gibb": [20, 27], "gif": 4, "gini": 10, "gini_index": 9, "ginvers": 13, "git": [0, 15, 20, 27], "giter": [13, 30], "github": [0, 20, 22, 23, 25, 26, 27, 28], "gitignor": 15, "gitlab": [0, 15, 20, 22, 27], "give": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 20, 22, 24, 27, 28, 29, 30], "given": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 21, 24, 27, 28, 29, 30], "global": [6, 7, 13, 29, 30], "glorot": 1, "gnew": 13, "go": [0, 1, 3, 5, 6, 8, 9, 11, 12, 13, 15, 16, 18, 27, 28, 29], "goal": [0, 7, 9, 27], "goe": [0, 1, 2, 5, 6, 13, 14, 15, 19, 21, 27, 28, 29, 30], "golden": 13, "gone": [5, 28, 29], "gong": 1, "good": [1, 3, 4, 5, 6, 9, 10, 11, 13, 15, 18, 20, 24, 26, 28, 29, 30], "goodfellow": [4, 26, 27, 28, 29], "googl": [1, 4, 20, 27], "got": [1, 6, 22], "gotten": 27, "gov": 6, "govern": 27, "gp": 26, "gpu": [1, 13, 20, 27], "grad": [2, 13, 30], "grad_analyt": 13, "grad_ol": 18, "grad_ridg": 18, "grade": [22, 23], "gradient": [0, 3, 4, 7, 8, 9, 12, 20, 27, 28], "gradient_desc": 30, "gradientboostingclassifi": 10, "gradientboostingregressor": 10, "gradients_of_discrimin": 4, "gradients_of_gener": 4, "gradienttap": 4, "gradual": [1, 14], "grai": [4, 6], "graph": [1, 9, 11, 12, 13, 16, 29], "graph_from_dot_data": 9, "graphic": [0, 1, 9, 15, 27], "grasp": 0, "gray_r": [1, 3], "grayscal": 3, "great": [5, 13, 15, 29, 30], "greater": [1, 7, 24, 28], "greatli": 13, "greedi": 9, "green": [0, 3, 9, 24], "grei": 4, "grid": [1, 3, 6, 7, 8, 12, 24, 28, 30], "grossli": [13, 29], "ground": [0, 27], "group": [0, 6, 7, 9, 14, 15, 20, 22, 23, 25, 27], "groupbi": [0, 27], "grow": [1, 3, 9, 10, 30], "growth": [0, 27], "gru": 4, "guarante": [0, 4, 13, 24, 27, 28, 29, 30], "guess": [1, 4, 10, 13, 14, 29, 30], "guestrin": 10, "gui": 15, "guid": 1, "h": [0, 1, 5, 6, 8, 13, 15, 19, 24, 25, 26, 27, 28, 29, 30], "h1": 2, "h_": [0, 13, 27, 29, 30], "h_0": 30, "h_1": [2, 13, 29], "h_2": [2, 13, 29], "h_m": 10, "h_t": 30, "ha": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "haanen": [25, 27], "habit": [0, 28], "had": [0, 1, 6, 7, 13, 27, 29, 30], "hadamard": [1, 12, 13, 30], "half": [1, 8, 9], "halv": 10, "hand": [0, 1, 2, 3, 5, 11, 12, 13, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30], "handi": [3, 22], "handl": [0, 1, 2, 5, 9, 11, 15, 18, 20, 28, 29, 30], "handle_unknown": 9, "handsid": 12, "handwrit": 12, "handwritten": [1, 5], "happen": [1, 2, 3, 4, 5, 6, 10, 13, 24, 28, 29, 30], "hard": [1, 7, 8, 10, 13, 29, 30], "hardcopi": [20, 27], "harder": [0, 1, 28], "harmon": 3, "hasn": [], "hassl": [0, 20, 27], "hast": [20, 27], "hasti": [0, 6, 16, 17, 19, 22, 26, 27, 28], "hat": [0, 1, 5, 6, 7, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 28, 29, 30], "have": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "haven": 1, "he": 7, "head": [4, 10, 24], "header": [0, 27], "heads_proba": 10, "health": [0, 28], "hear": [0, 13, 27, 30], "heart": [0, 7, 27], "heatmap": [0, 1, 3, 7, 17, 27], "heavili": 0, "heavisid": 1, "height": [1, 3, 6, 28], "held": [13, 30], "help": [0, 1, 4, 12, 13, 15, 16, 22, 27, 30], "helper": [4, 14], "henc": [0, 5, 6, 8, 9, 10, 12, 13, 27, 28, 29, 30], "henrik": [25, 27], "her": 7, "here": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "hereaft": [0, 8, 12, 27], "hermitian": 21, "hessenberg": 21, "hessian": [0, 2, 5, 13], "heterogen": [9, 10], "hi": 7, "hidden": [1, 3, 4, 12], "hidden_bia": 1, "hidden_bias_gradi": 1, "hidden_layer_s": [0, 1, 27], "hidden_neuron": 4, "hidden_weight": 1, "hidden_weights_gradi": 1, "hierarch": [5, 28, 29], "high": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 13, 14, 20, 21, 22, 27, 28, 29, 30], "higher": [0, 1, 3, 5, 6, 8, 13, 18, 22, 27, 28, 29, 30], "highest": [1, 2], "highli": [0, 3, 4, 10, 19, 20, 21, 26, 27, 28, 29, 30], "highwai": [], "hing": 8, "hint": [13, 15, 16, 28, 29], "hinton": 30, "hip": 20, "hire": 0, "hist": [4, 6, 7, 24], "histogram": [6, 7, 24], "histor": [7, 11], "histori": [3, 4, 12, 15, 30], "hitherto": 5, "hjorth": [25, 27, 28, 29, 30], "hobbi": 24, "hoc": [5, 28, 29], "hoff": 26, "hold": [1, 3, 6, 13, 14, 29, 30], "holder": [0, 27], "home": [], "homepag": [22, 27], "homework": [6, 13, 29, 30], "homogen": [1, 3, 9, 10, 13, 30], "honchar": 2, "hopefulli": [0, 11, 15, 24, 27, 30], "horizont": 11, "horlyk": [25, 27], "hors": [3, 7, 27], "hot": [1, 9], "hour": [1, 20, 23, 24, 25, 27], "how": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "howev": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 24, 27, 28, 29, 30], "hspace": [0, 4, 8, 10, 24, 27], "hstack": 1, "htf": 27, "html": [0, 16, 20, 22, 23, 25, 26, 27, 28, 29, 30], "http": [0, 3, 4, 6, 13, 15, 16, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30], "huang": [0, 27], "huber": [0, 27], "huge": [1, 3, 4, 20], "human": [0, 1, 3, 6, 9, 12, 28], "humid": 9, "hundr": 1, "hungri": 1, "hybrid": 23, "hydrogen": [0, 27], "hyperbol": [1, 4, 12], "hyperparam": 8, "hyperparamet": [3, 4, 5, 6, 9, 13, 18, 22, 28, 29, 30], "hyperplan": 11, "h\u00f8rlyk": [25, 27], "i": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30], "i0": [0, 27], "i1": [0, 6, 8, 12, 27, 28, 30], "i2": [0, 8, 12, 27], "i3": [0, 12, 27], "i5": [0, 27], "i_": [13, 29, 30], "i_1": [5, 6], "i_2": [5, 6], "i_t": 30, "ian": 26, "ic": [1, 22], "id": [7, 13, 29, 30], "ida": [25, 27], "idea": [0, 1, 2, 3, 4, 6, 9, 10, 12, 13, 21, 22, 28, 29, 30], "ideal": [0, 2, 6, 8, 13, 24, 27, 30], "idem": 6, "ident": [5, 6, 12, 13, 17, 18, 21, 28, 29], "identifi": [0, 1, 7, 9, 11, 12, 13, 14, 27, 28], "ieor": 24, "ifi": 26, "ifs": [20, 27], "ignor": [0, 1, 3, 9, 15, 28, 30], "ii": [21, 24], "iii": [21, 27], "ij": [0, 1, 3, 6, 8, 12, 14, 16, 21, 24, 27, 28, 30], "ik": [0, 21, 27, 28], "ill": 30, "illustr": [5, 7, 10, 12, 13, 14, 20, 27], "ilsvrc": 30, "im": 6, "imag": [1, 3, 4, 6, 9, 11, 12, 14, 26, 27], "image_at_epoch_": 4, "image_batch": 4, "image_height": 3, "image_path": [0, 6, 7, 9, 27], "image_width": 3, "imageio": 6, "images_from_seed_imag": 4, "imagin": 1, "immedi": [0, 3, 4, 6, 20, 27], "implement": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 22, 24, 27, 28, 29, 30], "impli": [3, 5, 6, 7, 13, 21, 28, 29, 30], "implicit": 3, "implicitli": [11, 24], "import": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 24, 30], "importantli": 3, "impos": [0, 6, 11, 12, 27], "imposs": [0, 5, 27, 28, 29], "impress": [0, 12, 27], "improv": [0, 4, 5, 9, 10, 11, 13, 15, 22, 28, 29], "impur": 9, "imread": 6, "imshow": [1, 3, 4, 6], "in3050": [26, 27], "in3310": 27, "in4080": [26, 27], "in4300": [26, 27], "in4310": 26, "in5400": 3, "in5550": 26, "in_out_neuron": 4, "inaccur": [13, 29], "inact": 12, "inadequ": [0, 27], "inappropri": 30, "inch": [6, 28], "includ": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 15, 16, 17, 18, 20, 24, 25, 26, 27, 28, 29], "include_bia": [6, 9], "incom": [12, 16], "incorrect": 1, "incoveni": 8, "increas": [0, 1, 3, 4, 5, 6, 9, 12, 13, 19, 22, 24, 27, 28, 30], "increasingli": 24, "increment": 30, "ind": 6, "inde": [0, 2, 4, 5, 6, 13, 27, 28, 29], "indefinit": 4, "independ": [0, 5, 6, 7, 8, 12, 13, 24, 27, 28, 29], "index": [0, 1, 3, 4, 10, 14, 20, 21, 22, 24, 26, 27], "index_col": [0, 27], "indic": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 16, 22, 27, 28], "indispens": 6, "individu": [1, 6, 7, 10, 12, 24, 27, 28, 30], "indu": [], "indx": 21, "indx1": 2, "indx2": 2, "indx3": 2, "ineffici": [3, 13], "inequ": [8, 13], "inequaltii": 29, "inertia": 13, "inf1000": [20, 27], "inf1100": [20, 27], "inf1100l": [20, 27], "inf1110": [20, 27], "inf3000": 27, "infeas": 9, "infer": [0, 1, 4, 6, 26, 27], "inferenc": 1, "infil": [0, 6, 7, 9, 27], "infin": [5, 6, 7, 11, 19, 28, 29], "infinit": [3, 30], "infinitesim": 24, "influenc": [6, 10, 18], "influenti": 1, "info": 27, "inform": [0, 1, 3, 4, 6, 9, 11, 12, 13, 14, 21, 22, 26, 27, 29, 30], "inforom": 15, "infrequ": 30, "infti": [3, 6, 13, 24, 29], "ingeni": [13, 29, 30], "ingredi": [0, 9, 27], "inher": 6, "inherit": [21, 27, 30], "initi": [0, 1, 2, 6, 10, 13, 14, 18, 21, 24, 27, 29, 30], "inject": 14, "inlin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 24, 27, 28, 29, 30], "inner": [0, 13, 28], "inp": 4, "inplac": 13, "input": [0, 1, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 22, 24, 27, 28, 29, 30], "input_dim": 1, "input_shap": [3, 4], "inputs": 1, "inputs_shuffl": [0, 1, 28], "insert": [3, 5, 6, 8, 10, 24, 28, 29], "insid": [4, 7], "insight": [0, 1, 5, 20, 27, 28, 29], "insist": [6, 13, 28, 30], "inspir": [0, 1, 12, 22, 27], "instabl": 2, "instal": [0, 1, 5, 6, 9, 15], "instanc": [0, 1, 2, 4, 6, 9, 11, 13, 16, 27, 28, 29], "instanti": 10, "instead": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 17, 21, 24, 27, 28, 30], "institut": 1, "instruct": [0, 1, 15], "int": [0, 1, 2, 3, 4, 5, 6, 11, 13, 14, 21, 24, 28, 30], "int32": 10, "int_": [3, 6, 24], "int_0": 24, "int_a": 24, "intak": [0, 28], "integ": [1, 2, 13, 14, 21, 24, 27], "integer_vector": 1, "integr": [3, 6, 24, 27], "intellig": [0, 14, 26, 27], "intend": 10, "intens": [1, 18], "intention": 14, "interact": [0, 6, 9, 12, 20, 22, 27], "intercept": [0, 6, 8, 11, 13, 16, 17, 18, 27, 28, 29, 30], "intercept_": [0, 6, 8, 9, 13, 27, 28, 30], "interchang": [5, 12, 21], "interconnect": 1, "interesit": 19, "interest": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 20, 22, 24, 27, 28, 29], "interfac": [0, 1, 15, 21, 28], "interior": [0, 9, 27], "intermedi": [21, 28], "intern": [1, 10, 12], "interpol": [1, 3, 4, 6, 12], "interpr": [5, 28, 29], "interpret": [0, 1, 6, 9, 10, 12, 13, 15, 16, 19, 21, 22, 24], "interv": [0, 3, 5, 6, 7, 13, 19, 24, 27, 28, 29], "intial": [13, 29], "intract": [0, 4, 28], "intrins": [3, 11, 21, 24, 27], "intro": [20, 26, 27], "introduc": [0, 1, 5, 6, 8, 10, 12, 21, 22, 24, 27, 29, 30], "introduct": [1, 2, 4, 13, 26, 28, 29, 30], "introductori": [0, 4, 21, 26, 27, 28], "intuit": [0, 5, 6, 8, 12, 13, 22, 27, 30], "inv": [0, 5, 13, 17, 27, 28, 29, 30], "invalu": [0, 13, 20, 27, 29], "invari": 1, "invd": 5, "inver": 8, "invers": [0, 3, 6, 13, 27, 28, 29, 30], "inverse_transform": 8, "invert": [0, 5, 7, 10, 13, 16, 18, 27, 30], "invh": [13, 30], "invok": 8, "involv": [0, 2, 6, 7, 11, 12, 27, 28, 30], "io": [0, 20, 22, 23, 25, 26, 27, 28], "ip": [0, 8, 24, 27], "ipca": 11, "ipynb": [20, 27], "ipython": [0, 5, 7, 9, 11, 14, 20, 22, 27, 28], "iq": 6, "iri": [8, 9], "irreduc": 6, "irrelev": [5, 28, 29], "irrespect": [0, 27], "irvin": 22, "iseffici": [], "isn": 5, "isnul": [], "isomap": 11, "issu": [1, 9, 15, 21, 30], "it_arrai": 13, "item": [0, 13, 27], "items": [21, 27], "iter": [1, 2, 4, 6, 8, 13, 14, 18, 22, 24, 29, 30], "its": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 20, 21, 22, 24, 27, 29, 30], "itself": [5, 6, 12, 19, 22, 24, 27, 28], "j": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 21, 22, 24, 26, 27, 28, 29, 30], "j1": 21, "j_": 6, "j_lasso_sk": 6, "j_ridge_sk": 6, "j_sk": 6, "jackknif": [6, 20, 27], "jacobian": [2, 13, 29], "jason": 4, "jax": [20, 27, 30], "jensen": [25, 27, 28, 29, 30], "jerom": [19, 22, 26], "ji": [12, 21], "jit": 13, "jj": [0, 5, 6, 27], "jk": [0, 1, 6, 12, 21, 27], "jl": [0, 27], "jm": 21, "jnp": 13, "job": [2, 8, 10, 15], "join": [0, 4, 6, 7, 9, 27], "joint": [4, 5], "judg": [13, 29], "judgement": 6, "julia": [20, 21, 22], "jump": 24, "junk": 4, "jupit": 27, "jupyt": [0, 15, 16, 20, 22, 26, 27], "just": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 24, 27, 28, 29, 30], "justif": 0, "justifi": [3, 10], "k": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 22, 24, 25, 27, 28, 29, 30], "k0": 7, "k1": 7, "kaggl": [6, 22], "kappa_d": 24, "karl": [25, 27], "karush": 8, "katrin": [25, 27], "keep": [0, 1, 4, 5, 6, 11, 13, 14, 15, 18, 21, 22, 27, 28, 29, 30], "keepdim": [1, 6, 10, 21], "kei": [1, 3, 6, 12], "kept": [4, 6, 14], "kera": [0, 4, 20, 22, 27], "kernel": [0, 1, 3, 20, 27, 28], "kernel_regular": [1, 3], "kernel_s": 4, "kernelpca": 11, "kev": [0, 27], "kevin": [26, 27], "keyword": [18, 21, 27], "kfold": 6, "kg": 1, "ki": 21, "kick": [1, 13, 30], "kiener": 2, "kilomet": [6, 28], "kind": [0, 2, 3, 4, 8, 12, 13, 14, 27, 28], "kingma": 30, "kj": [6, 12, 21, 28, 30], "kjm": [20, 27], "kkt": 8, "kl": 24, "km": [12, 27], "kmean": 14, "kmeanspoint": 14, "kn_k": 14, "know": [0, 1, 2, 5, 6, 8, 13, 15, 16, 17, 19, 20, 27, 28, 29], "knowledg": [0, 20, 27], "known": [1, 3, 4, 5, 6, 7, 8, 9, 12, 18, 21, 22, 24, 26, 28, 30], "kondev": [0, 27], "kp": 24, "kpca": 11, "kroneck": 14, "kuhn": 8, "kvalsund": [25, 27], "kwown": [0, 27], "l": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 21, 22, 24, 27, 29], "l0": 7, "l1": [0, 1, 3, 7, 27], "l1_l2": [1, 3], "l1regl": 5, "l2": [1, 3], "l_": 21, "l_1": 7, "l_2": [7, 13, 29, 30], "l_j": 12, "la": 13, "la_i": 12, "la_k": 12, "lab": [20, 22, 27], "label": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 20, 21, 22, 24, 27, 28, 29, 30], "labelencod": [7, 10], "labels": [6, 8, 9], "labels_shuffl": [0, 1, 28], "laboratori": 23, "lack": [0, 27], "lagari": 2, "lagrang": [8, 11], "lam": 18, "lambda": [0, 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 17, 18, 19, 22, 24, 27, 28, 29, 30], "lambda_": 11, "lambda_0": 11, "lambda_1": [5, 8, 11, 28, 29], "lambda_2": [8, 11], "lambda_i": [8, 11], "lambda_iy_i": 8, "lambda_jy_iy_j": 8, "lambda_k": 8, "lambda_n": [5, 8, 28, 29], "lamda": 1, "land": 8, "landmark": 8, "landscap": [13, 18, 29, 30], "langl": [0, 6, 11, 24, 27, 28], "languag": [0, 1, 4, 8, 20, 21, 22, 26, 27], "lapack": [21, 27], "laplac": 5, "laptop": [15, 20], "larg": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 13, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30], "larger": [0, 3, 5, 6, 8, 10, 11, 13, 17, 24, 27, 28, 29, 30], "largest": [4, 8, 11], "lasso": [0, 7, 20, 27, 30], "lasso_sk": 6, "last": [0, 1, 3, 4, 5, 6, 7, 8, 12, 16, 17, 19, 21, 22, 24, 25, 27, 29], "latent": 4, "latent_dim": 4, "latent_point": 4, "latent_space_value_rang": 4, "later": [0, 1, 4, 7, 8, 12, 13, 14, 15, 20, 22, 27, 30], "latest": [4, 15, 20], "latest_checkpoint": 4, "latex": 27, "latter": [0, 3, 6, 7, 8, 11, 13, 21, 24, 27, 28, 29, 30], "lattic": 12, "law": 0, "layer": [0, 4, 13, 27, 30], "lbfg": [7, 9, 10], "lcc": [5, 6], "lda": 11, "ldot": [0, 6, 11, 22, 27], "le": [5, 7, 10, 13, 17, 24, 28, 29], "lead": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 21, 24, 27, 28, 29, 30], "leaf": 9, "leaki": 1, "leakyrelu": 4, "lear": [13, 29], "learn": [3, 4, 5, 6, 7, 8, 9, 10, 12, 21, 25, 26], "learnabl": 3, "learner": 10, "learnig": 27, "learning_r": [8, 10], "learning_rate_init": [0, 1, 27], "learning_schedul": [13, 30], "learnt": 22, "least": [0, 7, 8, 10, 11, 17, 18, 20, 21, 24], "leat": [13, 30], "leav": [0, 1, 3, 5, 6, 9, 11, 27, 29], "lectur": [0, 1, 5, 10, 11, 12, 13, 20, 21, 22, 23, 25, 26, 28], "lecturenot": [0, 20, 22, 26, 27], "left": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "leftarrow": [8, 12], "legend": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 15, 27, 28, 29, 30], "leinonen": 27, "len": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 16, 17, 21, 27, 28, 29, 30], "length": [0, 1, 3, 4, 8, 9, 13, 16, 20, 27, 28, 29, 30], "length_of_sequ": 4, "leq": [0, 5, 7, 8, 13, 14, 24, 27, 28, 29, 30], "less": [0, 1, 3, 4, 5, 6, 8, 9, 13, 20, 24, 27, 28, 29, 30], "lessen": 1, "let": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, 21, 24, 27, 28, 29, 30], "letter": [0, 16, 21, 24, 27, 28], "level": [0, 1, 5, 6, 9, 20, 21, 22, 23, 25, 27], "leverag": 30, "li": [8, 11], "lib": [], "liberti": 30, "liblinear": 10, "librari": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 21, 22, 24, 26, 28, 29, 30], "licens": [0, 1, 20, 22, 27], "lie": [0, 6, 11, 24, 27, 28], "life": [0, 1, 8, 12, 27], "lifetim": 13, "like": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 29, 30], "likelihood": [0, 1, 5, 9, 27, 28], "lim_": 24, "limit": [0, 5, 6, 8, 12, 21, 22, 27, 28], "lin_clf": 8, "lin_model": [], "lin_reg": 9, "linalg": [0, 2, 5, 6, 8, 11, 13, 17, 21, 24, 27, 28, 29, 30], "line": [0, 3, 6, 8, 11, 13, 15, 16, 27, 29, 30], "line1": 8, "line2": 8, "line3": 8, "line_model": 15, "line_ms": 15, "line_predict": 15, "linear": [1, 3, 5, 6, 7, 9, 10, 11, 12, 16, 17, 18, 19, 20, 22, 24, 30], "linear_model": [0, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 27, 28, 29, 30], "linear_regress": 6, "linearli": [5, 28, 29], "linearloc": [6, 13, 29, 30], "linearregress": [0, 6, 7, 9, 15, 16, 19, 27, 28, 30], "linearsvc": 8, "lineat": 29, "liner": [1, 3], "linerar": 10, "linewidth": [0, 2, 4, 6, 8, 9, 10], "link": [0, 4, 9, 12, 15, 20, 22, 23, 25, 27], "linlag": 5, "linpack": [21, 27], "linreg": [0, 27], "linspac": [0, 2, 3, 4, 6, 8, 9, 10, 13, 16, 17, 19, 21, 24, 27, 28, 30], "linu": 4, "linux": [0, 1, 20, 22, 27], "liquid": [0, 27], "list": [1, 2, 3, 4, 9, 15, 20, 22, 27, 30], "listedcolormap": [9, 10], "literatur": [1, 7, 14, 26], "littl": [1, 3, 9, 12, 30], "live": [8, 16], "ll": [0, 18, 24, 27, 28], "lle": [0, 28], "lloyd": [4, 14], "lmb": [0, 2, 5, 6, 28, 29, 30], "lmbd": [0, 1, 3, 27], "lmbd_val": [0, 1, 3, 27], "lmbda": [13, 29, 30], "ln": [1, 13, 29], "load": [1, 4, 6, 7, 9, 10], "load_boston": [], "load_breast_canc": [1, 7, 9, 10, 11], "load_data": [3, 4], "load_digit": [1, 3], "load_iri": [8, 9], "loc": [3, 6, 7, 8, 9, 10, 27], "local": [0, 1, 3, 7, 12, 13, 15, 28, 29, 30], "locat": [2, 3, 8, 15], "log": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 13, 15, 21, 22, 27], "log10": [0, 5, 6, 28, 29, 30], "log_": [0, 27], "log_clf": 10, "logarithm": [0, 5, 7, 17, 21, 27], "logbook": 22, "logic": [0, 1, 9, 27], "login": 15, "logist": [0, 1, 2, 8, 9, 10, 11, 12, 13, 20, 28, 29, 30], "logisticregress": [7, 9, 10, 11], "logit": 7, "logreg": [7, 9, 10, 11], "logspac": [0, 1, 3, 5, 6, 27, 28, 29, 30], "long": [0, 1, 3, 4, 12, 13, 27, 29, 30], "longer": [2, 3, 8, 10, 14, 21, 24, 27, 30], "loocv": 6, "look": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 21, 22, 24, 27, 28, 29, 30], "loop": [1, 4, 6, 10, 12, 14, 16, 17, 18, 20, 21, 27], "lose": 1, "loss": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 13, 18, 21, 22, 27], "loss_fil": 4, "lossfil": 4, "lost": 4, "lot": [1, 4, 6, 16, 30], "low": [0, 6, 9, 10, 11, 22, 27, 28], "lower": [0, 1, 3, 6, 9, 10, 16, 21, 28], "lowercas": [21, 27], "lowest": [9, 13, 24, 30], "lr": [1, 3, 4, 10], "lstat": [], "lstm": 4, "lstm_2layer": 4, "lstsq": [0, 27, 28], "lt": 6, "lu": [0, 5, 27, 28, 29], "lubksb": 21, "luckili": 2, "ludcmp": 21, "lux": 21, "lvert": 1, "lw": [0, 27], "m": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 15, 21, 24, 25, 26, 27, 28, 29, 30], "m_": [9, 12], "m_0": 30, "m_1": 14, "m_h": [0, 27], "m_k": 14, "m_l": 12, "m_n": [0, 27], "m_p": [0, 27], "m_t": [13, 30], "ma": 11, "machin": [1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 15, 16, 21, 26, 28], "machinelearn": [0, 6, 16, 20, 22, 23, 25, 26, 27, 28, 29], "mackai": 26, "made": [0, 1, 3, 4, 5, 6, 7, 9, 11, 12, 22, 27, 28], "mae": [0, 27], "magic": 4, "magnitud": [1, 6, 7, 13, 28, 30], "mai": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 19, 20, 21, 22, 24, 27, 28, 29, 30], "mail": [23, 25], "main": [0, 1, 3, 4, 5, 6, 7, 9, 21, 22, 26, 28, 29, 30], "mainli": [0, 5, 6, 7, 9, 27, 28], "maintain": [6, 30], "major": [1, 6, 9, 10, 13, 21, 27, 29, 30], "make": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 18, 20, 21, 22, 24, 26, 27, 29, 30], "make_axes_locat": 6, "make_moon": [8, 9, 10], "make_pipelin": [0, 6, 10, 28], "makedir": [0, 6, 7, 9, 27], "malcondit": 21, "malign": [1, 7, 9], "mammographi": 5, "manag": [0, 2, 3, 15, 20, 22, 27], "mandatori": [25, 27], "mani": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 26, 27, 28, 29, 30], "manifold": 11, "manner": 3, "manual": [6, 28, 30], "map": [0, 1, 2, 6, 7, 8, 11, 12, 14, 24, 27], "marc": 28, "margin": [0, 5, 8], "marit": [0, 27], "mark": 27, "marker": [7, 21, 27], "markov": [20, 27], "marsaglia": 24, "mass": [0, 1, 5, 13, 28, 29], "massag": [0, 27], "masses2016": [0, 27], "masses2016ol": [0, 27], "masses2016tre": 0, "masseval2016": [0, 27], "master": [23, 25], "mat": [20, 27], "mat1100": [20, 27], "mat1110": [20, 27], "mat1120": [20, 27], "match": [1, 4, 5, 13, 14, 15, 28, 29, 30], "materi": [4, 5, 7, 13, 15, 21, 23, 25], "math": [3, 7, 12, 13, 21, 24, 26, 27, 30], "mathbb": [0, 4, 5, 6, 7, 8, 11, 12, 13, 14, 17, 19, 21, 22, 24, 27, 28, 29, 30], "mathbf": [0, 5, 6, 7, 8, 13, 19, 21, 22, 27, 28, 29, 30], "mathcal": [1, 5, 6, 7, 13, 22], "matheemat": 3, "mathemat": [0, 6, 11, 12, 13, 20, 21, 24, 26, 27, 30], "mathemati": 27, "mathrm": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 22, 24, 27, 28, 29, 30], "matmul": [1, 2, 5], "matnat": 26, "matplotlib": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 20, 21, 22, 24, 27, 28, 29, 30], "matric": [0, 1, 3, 4, 6, 7, 8, 11, 13, 16, 17, 20, 28, 29], "matrix": [0, 2, 3, 4, 6, 7, 8, 10, 13, 17, 18, 19, 22, 24], "matshow": 1, "matter": [2, 3, 13, 28, 29, 30], "max": [0, 1, 2, 3, 4, 9, 10, 12, 13, 25, 27, 29, 30], "max_depth": [0, 9, 10], "max_diff": 2, "max_diff1": 2, "max_diff2": 2, "max_it": [0, 1, 8, 13, 27], "max_iter": 14, "max_leaf_nod": 10, "max_sampl": 10, "maxdegre": [0, 6, 10, 28], "maxdepth": 10, "maxim": [1, 4, 5, 7, 8, 11], "maximum": [0, 2, 3, 5, 7, 8, 9, 10, 13, 14, 27, 28, 29, 30], "maxpolydegre": [5, 6, 28, 29, 30], "maxpooling2d": 3, "mbox": [5, 6, 28, 29], "mcculloch": 12, "md": 11, "mdoel": 4, "mean": [1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 27, 30], "mean_absolute_error": [0, 27], "mean_divisor": 14, "mean_i": 24, "mean_matrix": 14, "mean_squared_error": [0, 4, 6, 7, 10, 15, 19, 27, 28], "mean_squared_log_error": [0, 27], "mean_vector": 14, "mean_x": 24, "meaning": [0, 4, 7, 27], "meansquarederror": [0, 27], "meant": [3, 7, 10, 13], "meanwhil": 30, "measur": [0, 1, 2, 5, 6, 9, 11, 12, 14, 16, 18, 19, 22, 24, 27, 28, 30], "mechan": [0, 4, 24, 27, 30], "median": [0, 27, 28, 30], "medicin": 12, "medium": [4, 8, 13], "medv": [], "meet": [0, 25], "mehta": [0, 27, 28, 29], "memori": [3, 4, 11, 12, 13, 18, 21, 30], "mention": [0, 12, 13, 22, 24, 27, 29, 30], "mere": [0, 22], "meshgrid": [2, 5, 6, 8, 9, 10, 11], "mess": 15, "messag": [5, 13], "messi": 2, "met": [0, 3, 8, 28], "meteorolog": 9, "meter": [6, 28], "method": [0, 1, 2, 3, 4, 5, 7, 8, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 24, 26, 28], "metion": 6, "metric": [0, 1, 3, 6, 7, 9, 10, 14, 15, 19, 27, 28], "metropoli": [20, 27], "mev": [0, 24, 27], "mgd": [13, 30], "mglearn": [20, 27], "mgrid": 13, "mhjensen": [], "mi": 10, "mia": [25, 27], "microsoft": 26, "mid": 1, "midel": 4, "midnight": 15, "midpoint": 9, "might": [0, 1, 2, 4, 6, 9, 13, 15, 17, 18, 28, 29, 30], "migth": 17, "mild": 9, "millimet": [6, 28], "million": [0, 27, 28, 30], "mimic": 12, "min": [0, 2, 5, 8, 9, 29], "min_": [0, 2, 5, 14, 17, 27, 28, 29], "min_samples_leaf": 9, "mind": [0, 6, 13, 15, 18, 27, 28, 29, 30], "mindboard": 4, "mine": [20, 27], "mini": [1, 11, 12, 13, 29], "minibatch": [1, 11, 13], "minibathc": [13, 30], "miniforge3": [], "minim": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 28, 29, 30], "minima": [0, 1, 7, 13, 27, 29, 30], "minimum": [0, 1, 2, 6, 8, 9, 11, 13, 28, 29, 30], "minmaxscal": [0, 28, 30], "minor": 24, "minst": 1, "minu": 7, "mirjalili": 27, "mirror": 9, "misc": 6, "misclassif": [8, 9, 10], "misclassifi": [8, 10], "miser": 0, "mismatch": 1, "miss": [7, 10], "mistak": 4, "mit": 26, "mix": [1, 2, 27], "mixtur": [13, 30], "mk": [9, 21], "mkdir": [0, 6, 7, 9, 27], "ml": [0, 1, 10, 13, 21, 22, 28, 29, 30], "mlab": 24, "mle": [5, 7], "mlp": 1, "mlpclassifi": 1, "mlpregressor": [0, 27], "mm": 21, "mml": 28, "mn": [12, 24], "mnist": [1, 11], "mod": 24, "mode": [23, 25, 27], "model": [2, 3, 5, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 20, 22, 24, 26, 28, 29, 30], "model_select": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "moder": [10, 30], "modern": [0, 6, 7, 20, 27], "modif": [2, 12, 13], "modifi": [0, 1, 3, 5, 7, 8, 10, 12, 13, 27, 28, 29, 30], "modul": [0, 16, 21, 27], "modular": 24, "modulo": 24, "moe": [11, 28], "moment": [5, 6, 13, 24], "mondai": [25, 27], "monitor": [13, 30], "monoton": [5, 12, 24], "mont": [0, 6, 20, 24, 26, 27], "montli": 16, "moor": [5, 6], "more": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 24], "moreov": [0, 3], "morten": [25, 27, 28, 29, 30], "mortenhj": 27, "most": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 20, 22, 24, 27, 28, 29, 30], "mostli": [1, 11, 18], "motion": [0, 13], "motiv": [1, 4], "move": [0, 4, 5, 6, 7, 9, 12, 13, 14, 15, 16, 22, 24, 28, 29], "mpl": [7, 27], "mpl_toolkit": [2, 6, 13, 29, 30], "mplot3d": [2, 6, 13, 29, 30], "mplregressor": 1, "mse": [0, 4, 5, 6, 9, 10, 15, 16, 17, 19, 22, 27, 28, 29, 30], "mse_simpletre": 10, "mselassopredict": [5, 29], "mselassotrain": [5, 29], "mseownridgepredict": [6, 28, 29, 30], "msepredict": [5, 29], "mseridgepredict": [0, 5, 6, 28, 29, 30], "msetrain": [5, 29], "msle": [0, 27], "mt": [7, 12], "mu": [0, 6, 11, 13, 24, 27], "mu0": 24, "mu1": 24, "mu2": 24, "mu_": [6, 24, 28, 30], "mu_i": [6, 28, 30], "mu_n": 11, "mu_x": 24, "much": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 21, 22, 24, 27, 28, 29, 30], "multi": [0, 1, 3, 7, 20, 27], "multiclass": [1, 7], "multidimension": [11, 12, 27], "multilay": 1, "multinomi": 7, "multipl": [2, 4, 5, 6, 7, 12, 13, 15, 24, 28, 29], "multipli": [3, 5, 6, 11, 13, 18, 21, 24, 28, 29, 30], "multiplum": 8, "multivari": [0, 2, 10, 11, 20, 24, 27], "multivariate_norm": [11, 14], "multpli": 16, "murphi": [11, 26, 27], "must": [1, 2, 5, 6, 8, 10, 12, 13, 14, 15, 24, 28, 29, 30], "mutat": 7, "mutual": [1, 3, 6, 13], "mx_": 24, "my": 27, "myenv": [], "myriad": [0, 20, 27], "mz1": 24, "mz2": 24, "m\u00f8svatn": 6, "n": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "n1": 21, "n2": 21, "n_": [1, 2, 3, 8, 12, 24], "n_0": [12, 24], "n_boostrap": [6, 10], "n_bootstrap": 6, "n_categori": [1, 3], "n_cluster": 14, "n_compon": 11, "n_epoch": [13, 30], "n_estim": 10, "n_examples_to_gener": 4, "n_featur": [1, 18], "n_filter": 3, "n_hidden": 2, "n_hidden_neuron": [0, 1, 27], "n_i": 24, "n_input": [0, 1, 3, 28], "n_instanc": 9, "n_iter": 30, "n_job": 10, "n_k": 14, "n_l": [12, 24], "n_layer": 1, "n_m": 9, "n_neuron": 1, "n_neurons_connect": 3, "n_neurons_layer1": 1, "n_neurons_layer2": 1, "n_point": 14, "n_sampl": [6, 8, 9, 10, 14, 18], "n_split": 6, "n_step": 4, "n_t": 2, "n_x": 2, "nabla": [1, 13, 29, 30], "nabla_": [2, 13, 29, 30], "nabla_w": 13, "nag": 13, "naimi": [0, 27], "naiv": 7, "naive_kmean": 14, "name": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 18, 20, 21, 22, 24, 25, 27, 28, 29], "narrow": [13, 30], "nation": [1, 5], "nativ": [20, 27], "natur": [0, 1, 4, 8, 9, 12, 13, 22, 24, 26, 27, 29, 30], "navier": 12, "navig": 15, "nb": 24, "nb_": 21, "nbconvert": 27, "nd": 14, "ndarrai": 6, "ne": [9, 10, 21, 24, 28, 29], "nearest": [1, 3, 6, 11], "nearli": [13, 29], "neat": 27, "neccesari": 6, "necess": 2, "necessari": [0, 1, 3, 4, 8, 14, 18, 27], "necessarili": [0, 4, 11, 24, 27], "necesserali": 5, "neck": 7, "need": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 24, 28, 29, 30], "neg": [0, 1, 3, 5, 6, 7, 10, 13, 21, 24, 27, 29], "neg_mean_squared_error": 6, "neglect": [24, 30], "neglig": 24, "neighbor": [3, 6, 11], "neither": [4, 13], "neq": [13, 14, 24, 29], "nervou": 12, "nest": [9, 12], "nesterov": 13, "net": [2, 4, 12], "netlib": [21, 27], "network": [0, 9, 13, 20, 26, 28, 30], "neural": [0, 13, 20, 26, 28, 30], "neural_network": [0, 1, 2, 27], "neuralnetwork": 1, "neuron": [1, 2, 3, 4, 12], "neutral": [0, 27], "neutron": [0, 27], "never": [1, 4, 6, 9, 24], "new": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 21, 27, 28, 29, 30], "new_chang": [13, 30], "new_hobbit": 27, "newaxi": [0, 3, 6, 9], "newli": [0, 27], "newton": [1, 7, 8, 13, 24], "next": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 27, 28, 29], "next_guess": 13, "next_input": 4, "ng": 1, "ni": 14, "nice": [0, 1, 5, 11, 27, 28, 29], "nicer": [18, 30], "niter": [13, 29, 30], "nitric": [], "nlambda": [0, 5, 6, 28, 29, 30], "nlp": 26, "nm": 24, "nm_n": [0, 27], "nmse": 6, "nn": [2, 5, 6, 12, 21, 27], "nn_model": 1, "nnmin": 2, "node": [1, 3, 9, 10, 12], "nois": [0, 4, 5, 6, 8, 9, 10, 13, 18, 19, 22, 27, 28, 29, 30], "noise_dimens": 4, "noisi": [1, 6, 22, 30], "non": [0, 1, 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 21, 24, 27, 28, 29, 30], "nondifferenti": 30, "none": [0, 1, 2, 4, 5, 9, 10, 13, 24, 27, 28], "nonlinear": [3, 6, 8, 9, 11, 12], "nonneg": [6, 9, 13, 29], "nonparametr": 6, "nonsens": 24, "nonsingular": 21, "nonumb": [3, 7, 8, 13, 21], "nor": [1, 4, 13], "norm": [0, 1, 5, 6, 8, 11, 13, 18, 27, 28, 29, 30], "normal": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "normali": [21, 27], "norwai": [6, 22, 27, 29, 30], "notat": [0, 2, 5, 6, 13, 14, 24, 27, 28, 29], "note": [0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 24, 26, 27, 30], "notebook": [0, 1, 3, 9, 15, 16, 20, 22, 27], "noth": [1, 2, 5, 8, 12, 14, 24, 28, 29], "notic": [4, 5, 12, 13, 21, 24, 27], "notion": 3, "novel": [3, 6, 10, 27], "novemb": [1, 25, 27], "now": [0, 2, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 19, 20, 21, 22, 24, 27, 28], "nowadai": [0, 1, 3, 9, 20, 27], "nox": [], "np": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 24, 27, 28, 29, 30], "npr": 2, "nsampl": 6, "nt": 2, "nu": 24, "nuclear": [5, 28, 29], "nuclei": [0, 24, 27], "nucleon": [0, 27], "nucleu": [0, 27], "num": 4, "num_coordin": 2, "num_hidden_neuron": 2, "num_it": [2, 18], "num_neuron": 2, "num_neurons_hidden": 2, "num_point": 2, "num_tre": 10, "num_valu": 2, "number": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 23, 25, 27, 29], "numberid": 7, "numberparamet": 3, "numer": [0, 5, 6, 9, 10, 11, 12, 13, 20, 21, 26, 27, 28, 29, 30], "numpi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 24, 28, 29, 30], "nunmpi": [5, 28], "nve_frngahw": 29, "nx": 2, "ny": 24, "o": [0, 1, 4, 5, 6, 7, 8, 9, 11, 21, 25, 26, 27, 28, 29], "obei": [6, 11, 13, 28, 30], "object": [0, 1, 4, 8, 10, 15, 19, 21, 27, 30], "obliqu": [5, 28, 29], "observ": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 24, 27, 29, 30], "obtain": [0, 1, 5, 6, 7, 8, 9, 10, 12, 13, 14, 17, 21, 22, 24, 27, 28, 29, 30], "obviou": [5, 6, 11, 24, 28, 29], "obviouli": 27, "obvious": [0, 4, 5, 6, 21, 27], "oc": [28, 29], "occupi": [], "occur": [0, 6, 8, 9, 21, 24, 27], "octob": [25, 27], "od": 0, "odd": [0, 3, 7, 27, 28, 30], "odenum": 2, "odesi": 2, "oen": 0, "off": [1, 3, 4, 5, 9, 13, 24], "offer": [6, 11, 20, 21, 23, 25, 27], "offic": [25, 27], "offici": [23, 27], "often": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 22, 24, 27, 28, 29, 30], "ofter": [21, 27], "ol": [0, 13, 17, 19, 28, 30], "old": [1, 5, 10, 13, 15, 18], "ols_paramet": 16, "ols_sk": 6, "ols_svd": 6, "olsbeta": 29, "olstheta": [0, 5], "omega": [2, 3, 6], "omega_0": 3, "omit": [0, 5, 27, 28, 29], "onc": [1, 6, 9, 11, 13], "one": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 19, 20, 21, 22, 24, 25, 27, 28, 30], "onehot": 1, "onehot_vector": 1, "onehotencod": 9, "ones": [0, 2, 5, 6, 8, 9, 10, 11, 13, 16, 18, 21, 22, 27, 28, 29, 30], "ones_lik": 4, "ong": 28, "onl": 3, "onli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 21, 22, 24, 27, 28, 29, 30], "onlin": [11, 15, 23], "onto": [5, 11, 28, 29], "open": [0, 1, 4, 6, 7, 9, 15, 20, 22, 23, 25, 27], "oper": [0, 1, 3, 5, 6, 10, 11, 12, 13, 15, 16, 20, 24, 27, 28, 29, 30], "operation": 24, "oplu": 24, "opmiz": [13, 30], "opportun": 0, "oppos": [6, 13], "opposit": [1, 5, 8, 28, 29], "opt": [1, 5, 22, 27, 29], "optim": [0, 2, 3, 4, 5, 6, 7, 9, 10, 11, 14, 16, 17, 19, 22], "optimis": [1, 3], "option": [0, 1, 3, 5, 6, 8, 11, 15, 18, 21, 28, 30], "optmiz": [1, 8, 13, 28], "oral": 27, "orang": 0, "order": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 15, 19, 21, 22, 24, 27, 28, 29], "ordinari": [0, 2, 3, 7, 11, 13, 17, 18, 20], "oreilli": [26, 27], "org": [0, 3, 4, 16, 20, 21, 22, 26, 27, 28, 29, 30], "organ": [6, 7, 10, 21], "orient": [1, 5, 24, 28, 29], "origin": [0, 3, 5, 6, 8, 11, 12, 13, 15, 21, 27, 28, 29, 30], "orthogn": [5, 28, 29], "orthogon": [0, 5, 6, 8, 11, 13, 21, 27, 28, 29], "orthonorm": [5, 28, 29], "os": [25, 27], "oscar": 1, "oscil": [3, 13, 30], "oskar": 27, "oskarlei": 27, "osl": 18, "oslo": [0, 20, 22, 23, 25, 27, 28, 29, 30], "osx": [0, 20, 22, 27], "other": [0, 1, 2, 3, 5, 6, 7, 8, 10, 13, 14, 16, 20, 23, 24, 25, 26, 28, 29, 30], "otherwis": [0, 1, 4, 7, 13, 21, 27, 30], "ouput": [5, 7, 12], "our": [1, 2, 3, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 18, 19, 20, 21, 24, 30], "ourmodel": 0, "ourselv": [0, 5, 6, 8, 11, 13, 27, 28, 29], "out": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 24, 27, 28, 30], "out_fil": 9, "outcom": [0, 7, 9, 10, 12, 24, 28], "outdoor": 9, "outer": [6, 12, 13], "outfil": 4, "outlier": [0, 8, 27, 28, 30], "outlin": [6, 10, 11], "outlook": 9, "outperform": [10, 30], "output": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 21, 22, 24, 27, 28, 29, 30], "output_bia": 1, "output_bias_gradi": 1, "output_shap": 4, "output_weight": 1, "output_weights_gradi": 1, "outputlayer1": 12, "outputlayer2": 12, "outsid": 4, "over": [0, 1, 3, 4, 5, 6, 9, 10, 12, 13, 15, 16, 21, 22, 27, 28, 29, 30], "over1": 13, "overal": [1, 10, 30], "overcast": 9, "overcom": [12, 13], "overdetermin": [0, 27], "overfit": [0, 1, 3, 6, 9, 10, 13, 30], "overflow": 5, "overhead": 12, "overlap": [3, 7, 8, 9], "overlin": [0, 5, 6, 9, 10, 11, 14, 21, 27, 28, 30], "overshoot": 30, "overst": 0, "overtrain": 4, "overview": 3, "own": [4, 5, 6, 8, 12, 13, 16, 18, 20, 21, 29, 30], "owner": [], "ownmsepredict": 0, "ownmsetrain": 0, "ownridgebeta": 28, "ownridgetheta": [0, 6, 28, 29, 30], "ownypredictridg": 0, "ownytilderidg": 0, "oxid": [], "p": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 24, 27, 28, 29, 30], "p0": 2, "p1": 2, "p_": [2, 4, 8, 9], "p_hidden": 2, "p_i": [5, 24], "p_j": 24, "p_n": 24, "p_output": 2, "p_x": 24, "pack": [0, 27], "packag": [0, 1, 3, 4, 5, 8, 11, 13, 15, 20, 22, 24, 28, 29, 30], "packtpub": 27, "packtpublish": 27, "pad": [3, 4], "page": [0, 20, 27, 29, 30], "pai": [0, 1, 9, 13, 15, 30], "pair": [0, 2, 3, 9, 20, 24, 27], "paltform": 15, "panda": [0, 4, 5, 6, 7, 9, 11, 20, 22, 29, 30], "panel": 27, "paper": [1, 30], "paradigm": [0, 27], "parallel": [10, 13, 20, 21, 27], "param": 2, "paramat": 2, "paramet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, 18, 19, 22, 24, 29, 30], "parameter": [0, 6, 10, 27, 28], "parametr": [0, 6, 27, 28], "paramt": [3, 5], "part": [0, 1, 3, 5, 6, 10, 17, 19, 21, 23, 24, 25, 27, 28], "partial": [0, 1, 5, 6, 7, 8, 10, 11, 12, 13, 16, 24, 27, 28, 29, 30], "particip": [15, 20, 23, 25, 27], "particl": [0, 4, 13, 24, 27], "particular": [0, 1, 2, 3, 5, 6, 9, 10, 11, 12, 13, 16, 22, 24, 26, 27, 28, 29, 30], "particularli": [5, 6, 8, 11, 13, 24, 28, 29, 30], "partit": [1, 4, 9], "partli": [6, 27], "partner": 15, "pass": [2, 3, 12, 14], "password": 22, "past": [10, 24, 30], "patch": [6, 24], "path": [0, 4, 6, 7, 9, 20, 27], "pathcollect": 17, "patient": 7, "patter": 4, "pattern": [0, 3, 4, 12, 26, 27], "pauli": [0, 27], "pc": [11, 15, 20], "pca": [0, 7, 20, 27, 28], "pd": [0, 4, 5, 6, 7, 9, 11, 27, 28, 29, 30], "pde": 2, "pdf": [0, 3, 4, 5, 6, 9, 15, 16, 22, 26, 27], "pedagog": [0, 27, 28], "penal": [6, 18, 28, 30], "penalti": [6, 13, 18, 22, 28, 30], "penros": [5, 6], "pentagon": [13, 29], "peopl": [1, 9, 13, 20, 30], "per": [0, 1, 6, 23, 25, 27, 30], "percentag": [10, 11, 25], "perceptron": [0, 1, 7, 27], "peregrin": 27, "perfect": [0, 1, 13, 27, 30], "perfectli": [4, 6], "perform": [0, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 14, 16, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "performac": 4, "perhap": [0, 5, 13, 27, 28, 29], "perimet": 1, "period": [1, 4, 24], "permiss": 15, "permut": 11, "persist": 13, "person": [5, 6, 7, 16, 23, 25, 27, 28], "perspect": 26, "pertin": [12, 27], "petal": [8, 9], "peter": [26, 28], "phantom": 24, "phase": [6, 12], "phenomena": 24, "phi": 8, "phi_k": 8, "philosophi": 13, "phone": [25, 27], "photo": [4, 27], "php": 22, "phrase": [0, 27], "physic": [0, 1, 4, 7, 12, 13, 24, 25, 26, 27, 28, 29, 30], "pi": [2, 3, 5, 6, 7, 9, 12, 13, 24], "pick": [1, 9, 10, 11, 13, 14, 30], "pickl": 1, "pictur": [0, 27], "pie": [20, 27], "piec": [11, 14], "pillow": [0, 20, 22, 27], "pinv": [5, 6, 13, 22, 28, 29, 30], "pip": [0, 1, 15, 20, 22, 27], "pip3": [0, 1, 22, 27], "pipelin": [0, 6, 8, 10, 28], "pippin": 27, "pit": 4, "pitfal": [6, 28], "pitt": 12, "pixel": [1, 3, 4, 27], "pixel_height": [1, 3], "pixel_width": [1, 3], "place": [0, 4, 6, 8, 13, 15, 21, 22, 27, 29], "plai": [0, 3, 4, 5, 6, 8, 11, 18, 20, 22, 27, 28, 29], "plain": [8, 10, 12, 13, 14, 29, 30], "plan": [6, 9, 25, 26, 27], "plane": [8, 9], "plateau": [5, 29], "platform": [20, 27], "plausibl": 12, "pleas": [13, 22, 25, 27], "plenti": 1, "plethora": [3, 12], "plot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 21, 22, 24, 27, 28, 29, 30], "plot_all_sc": [22, 28], "plot_confusion_matrix": [7, 10], "plot_count": 6, "plot_cumulative_gain": [7, 10], "plot_data": 1, "plot_dataset": 8, "plot_decision_boundari": [9, 10], "plot_import": 10, "plot_max": 4, "plot_min": 4, "plot_model": 4, "plot_numb": 4, "plot_predict": 8, "plot_regression_predict": 9, "plot_result": 4, "plot_roc": [7, 10], "plot_surfac": [2, 6, 13], "plot_train": 9, "plot_tre": [9, 10], "plt": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 24, 27, 28, 29, 30], "plu": [0, 3, 5, 7, 18, 27, 28], "pm": 8, "pmatrix": 2, "pml": 26, "pn": 3, "png": [0, 4, 6, 7, 9, 27], "point": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 21, 22, 24, 25, 27, 28, 29, 30], "point_1": 4, "point_2": 4, "poisson": [20, 24, 27], "poli": [6, 8], "poly100_kernel_svm_clf": 8, "poly3": 0, "poly3_plot": 0, "poly_featur": [8, 9, 15], "poly_features10": 9, "poly_fit": 9, "poly_fit10": 9, "poly_kernel_svm_clf": 8, "poly_model": 15, "poly_ms": 15, "poly_predict": 15, "polydegre": [0, 5, 6, 10, 28], "polygon": [13, 29], "polym": 12, "polymi": 22, "polynomi": [0, 5, 6, 7, 8, 9, 10, 11, 15, 17, 19, 22, 27, 28], "polynomial_featur": [6, 15, 16, 17], "polynomial_svm_clf": 8, "polynomialfeatur": [0, 6, 8, 9, 15, 16, 19, 28], "polytrop": [0, 6], "pool": 3, "pool_siz": 3, "poor": [1, 13, 29, 30], "poorli": [0, 28], "popul": [0, 5, 27, 28], "popular": [0, 1, 3, 6, 7, 8, 9, 11, 12, 15, 20, 21, 22, 24, 28], "popularli": [0, 27], "portabl": 10, "portion": [11, 13, 30], "pose": [0, 4, 5, 6, 11, 24, 27], "posit": [0, 1, 2, 3, 5, 7, 8, 10, 11, 13, 14, 21, 24, 27, 28, 29, 30], "possibl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20, 21, 22, 24, 25, 27, 28, 29, 30], "possibli": [6, 8, 13, 22], "posterior": 5, "postpon": [0, 28], "postscript": 22, "postul": 5, "potenti": [0, 3, 5, 6, 12, 13, 28, 30], "pott": 12, "power": [0, 1, 5, 6, 8, 9, 12, 13, 27, 28, 29, 30], "pp": [5, 6, 19], "practic": [0, 5, 6, 7, 8, 16, 18, 22, 24, 28], "practition": [0, 1, 3, 27], "pre": 27, "preced": [1, 11, 12, 24], "preceed": 4, "preceq": 8, "precis": [0, 2, 5, 11, 13, 21, 22, 24, 27, 28], "pred": 6, "predicit": 0, "predict": [0, 1, 5, 6, 7, 8, 9, 10, 15, 16, 17, 19, 20, 22, 26, 27, 28, 29, 30], "predict_prob": 1, "predict_proba": [7, 10], "predictor": [0, 5, 6, 7, 9, 10, 11, 27, 28, 30], "prefer": [0, 1, 6, 8, 9, 11, 13, 15, 20, 22, 27], "prepar": [0, 6, 21, 22, 27, 28], "preprocess": [0, 4, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18, 19, 22], "prerequisit": 0, "prescript": 22, "presenc": 13, "present": [0, 5, 6, 7, 9, 12, 13, 21, 22, 24, 27, 28, 29, 30], "preserv": [3, 11, 21], "press": [13, 15, 26, 29], "pretrain": [1, 4], "pretti": [0, 4, 8, 9, 20, 22, 27], "prev_centroid": 14, "prevent": [13, 24, 30], "previou": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 21, 22, 24, 28, 29, 30], "previous": [2, 3, 9, 10, 24], "price": [0, 4, 9, 13, 30], "primal": 8, "primari": [0, 7, 27], "prime": 24, "princip": [0, 5, 7, 20, 27, 28, 29], "principl": [0, 6, 7, 8, 14, 27], "print": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 21, 24, 27, 28, 29, 30], "print_funct": [8, 9], "printout": [0, 27], "prior": [0, 5, 6, 27], "privat": 0, "prob": [1, 24], "probabilist": [0, 26, 27, 28], "probabl": [0, 1, 3, 4, 6, 7, 10, 13, 20, 27, 28, 30], "problem": [0, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 19, 20, 21, 22, 24], "probml": 26, "proce": [0, 5, 6, 7, 8, 9, 10, 11, 13, 21, 27, 28], "procedur": [2, 4, 5, 6, 8, 10, 11, 13, 28, 29, 30], "proceed": 21, "process": [0, 2, 4, 6, 9, 10, 12, 13, 20, 21, 22, 24, 26, 27, 29, 30], "prod": 26, "prod_": [1, 5, 7], "produc": [0, 3, 4, 5, 6, 9, 10, 11, 12, 13, 18, 20, 21, 24, 27, 28], "product": [0, 1, 3, 5, 6, 7, 8, 12, 13, 16, 17, 20, 21, 27, 28, 30], "profess": [0, 27], "program": [0, 1, 4, 5, 6, 8, 12, 14, 15, 20, 21, 23, 24, 25, 27, 28], "programm": 21, "progress": [1, 4, 14, 30], "prohibit": 6, "project": [0, 1, 2, 3, 5, 11, 13, 15, 19, 20, 23, 28, 29, 30], "project_root_dir": [0, 6, 7, 9, 27], "promin": 12, "promis": 8, "promot": [25, 27], "prone": [9, 15], "pronounc": [13, 20, 27, 30], "proof": [0, 11, 12, 13, 27, 29], "prop": 30, "propag": [2, 3, 13, 30], "proper": [0, 2, 6, 7], "properli": [1, 6, 8, 10, 13, 18, 22, 30], "properti": [0, 1, 3, 12, 13, 16, 21, 27], "proport": [0, 1, 5, 9, 11, 13, 24, 27, 28], "propos": [1, 4, 6, 10, 22, 27, 30], "propto": [5, 13, 29, 30], "proton": [0, 27], "prove": [3, 13, 29, 30], "provid": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 20, 21, 22, 24, 27, 28, 29, 30], "proxi": [1, 13, 30], "prune": 9, "pseudo": [21, 24, 30], "pseudocod": 22, "pseudoinv": 5, "pseudoinvers": [5, 6, 22], "pseudorandom": [6, 24], "psychologi": [0, 27], "pt": 13, "public": [0, 15, 20, 27], "pull": 15, "punish": [0, 1, 27], "pure": [3, 9, 24], "purest": 9, "puriti": 9, "purpos": [0, 3, 10, 12, 14, 27], "push": 15, "put": 1, "py": 5, "pycod": 27, "pydata": 20, "pydot": 9, "pyhton2": 27, "pylab": [7, 27], "pypi": 20, "pyplot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 24, 27, 28, 29, 30], "pythagora": 5, "python": [1, 2, 3, 5, 6, 8, 11, 12, 13, 14, 18, 22, 24, 28, 30], "python2": [0, 22], "python3": [0, 20, 22, 27], "pytorch": [0, 20, 22, 27], "q": [5, 6, 8, 11, 24], "qp": 8, "qquad": [2, 11, 13, 21, 30], "qr": [5, 6, 21, 28, 29], "quad": [1, 13, 21], "quadrat": [0, 8, 9, 13, 27], "qualit": [4, 9, 22, 24], "qualiti": [0, 9, 20, 27, 28], "quantifi": 1, "quantil": 10, "quantit": [0, 6, 9, 22, 27], "quantiti": [0, 2, 5, 6, 7, 9, 10, 11, 12, 14, 16, 21, 24, 27, 28, 29, 30], "quantum": [4, 12, 26, 27], "quartil": [0, 28, 30], "quench": 5, "queri": 9, "question": [0, 5, 6, 9, 11, 12, 13, 22, 25, 27, 28, 30], "qugan": 4, "quick": [4, 24], "quickli": [1, 3, 9, 11, 13, 29], "quit": [1, 5, 6, 9, 10, 12, 15, 28, 29], "quot": 4, "r": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 20, 21, 22, 24, 28, 29, 30], "r2": [0, 5, 6, 27, 28, 29], "r2_score": [0, 27], "r2score": [0, 27], "r_": 30, "r_0": 30, "r_1": 9, "r_2": 9, "r_j": 9, "r_m": 9, "r_t": 30, "rad": [], "rade": [], "radial": [8, 12], "radioact": 24, "radiu": [0, 1, 28, 30], "rain": 9, "ramp": 1, "ran0": 24, "ran1": 24, "ran2": 24, "ran3": 24, "rand": [0, 4, 5, 6, 9, 10, 13, 15, 19, 21, 27, 28, 29, 30], "randint": [6, 9, 13, 30], "randn": [0, 1, 2, 5, 6, 9, 11, 13, 15, 18, 27, 28, 29, 30], "random": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 17, 18, 19, 20, 21, 27, 28, 29, 30], "random_forest_model": 10, "random_index": [13, 30], "random_indic": [1, 3], "random_st": [7, 8, 9, 10, 11], "randomforestclassifi": 10, "randomli": [1, 6, 9, 13, 14, 18, 29, 30], "rang": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 19, 21, 24, 27, 28, 29, 30], "rangl": [0, 6, 11, 24, 27, 28], "rangle_x": 24, "rank": [5, 28, 29], "rankdir": 4, "raphson": [1, 8, 13], "rapidli": 0, "rare": [1, 13, 30], "raschka": [27, 28], "rasckha": 27, "rashcka": [29, 30], "rate": [1, 2, 3, 4, 8, 9, 10, 12, 13, 18, 29], "rather": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 24, 27, 28, 29], "ratio": [4, 7, 9, 10, 11], "rational": [0, 27], "ravel": [5, 6, 7, 8, 9, 10, 11, 13, 21], "raw": [3, 30], "rbf": [8, 11, 12], "rbf_kernel_svm_clf": 8, "rbf_pca": 11, "rc": 24, "rcond": [0, 27, 28], "rcparam": [1, 3, 7, 8, 9, 10, 24, 27], "re": [2, 4, 13, 15, 29], "reach": [1, 4, 5, 6, 9, 10, 12, 13, 14, 29, 30], "read": [0, 2, 3, 4, 5, 6, 7, 8, 11, 12, 16, 17, 21, 22, 24, 26, 29], "read_csv": [0, 6, 7, 9], "read_fwf": [0, 27], "reader": [0, 6, 21, 24, 27, 28, 30], "readi": [0, 1, 5, 6, 8, 10, 11, 12, 21, 27], "readili": 1, "readm": 15, "readthedoc": 20, "real": [0, 1, 4, 7, 10, 11, 12, 16, 18, 19, 21, 28], "real_loss": 4, "real_output": 4, "realist": [8, 27], "realiti": 24, "realiz": [1, 12], "realli": [0, 1, 27], "rearrang": 13, "reason": [0, 1, 3, 4, 10, 13, 26, 27, 29, 30], "reassign": 1, "recal": [5, 6, 9, 10, 11, 12, 21, 24, 27, 28, 29, 30], "recast": 3, "receiv": [1, 3, 10, 12, 24], "recent": [0, 6, 13, 26, 30], "recept": [3, 12], "receptive_field": 3, "recip": [0, 6, 7, 21, 22, 27, 28], "reciproc": 5, "recogn": [0, 4, 5, 10, 27], "recognit": [0, 1, 3, 12, 26, 27], "recommen": 27, "recommend": [0, 2, 3, 4, 5, 6, 8, 13, 15, 19, 20, 21, 22, 26, 29, 30], "reconsid": 9, "reconstruct": 11, "record": [10, 22, 23, 25, 27], "recreat": 15, "rectangl": [9, 13, 29], "rectangular": [5, 28, 29], "rectifi": [1, 3, 12], "recur": [0, 20, 27], "recurr": [0, 1, 20, 27], "recurs": [9, 20, 21, 27], "red": [0, 3, 4, 6, 8, 9, 30], "redefin": [0, 10, 27, 28, 29], "redefinit": 29, "reduc": [1, 3, 5, 6, 9, 10, 11, 13, 27, 29, 30], "reduct": [0, 10, 11, 20, 24, 27, 28], "reegress": 22, "refer": [0, 1, 2, 3, 5, 6, 11, 12, 13, 14, 21, 26, 27, 28, 29, 30], "referenc": 2, "refin": 12, "refit": 6, "reflect": [0, 1, 4, 5, 22, 24, 27], "refresh": [20, 27], "refreshprogrammingskil": 27, "reg": [10, 11], "regard": [1, 9, 13], "regardless": [12, 16], "region": [3, 4, 6, 9, 12, 22], "regist": [6, 24], "reglasso": [5, 29], "regr_1": [0, 9], "regr_2": [0, 9], "regr_3": [0, 9], "regress": [1, 8, 11, 12, 16, 20, 21], "regressor": [0, 7, 10], "regret": [], "regridg": [0, 5, 6, 28, 29, 30], "regular": [0, 3, 4, 5, 6, 7, 9, 13, 17, 18, 25, 27, 28, 29, 30], "regularli": 15, "reilli": [0, 26, 27], "reinforc": [0, 8, 20, 27], "reiter": 1, "reject": 7, "rel": [0, 4, 6, 7, 9, 12, 13, 24, 27, 28, 30], "relat": [0, 1, 3, 4, 5, 11, 13, 14, 19, 21, 24, 27, 28, 29], "relationship": [0, 4, 9, 18, 27], "relativeerror": [0, 27, 28], "releas": [1, 20, 27], "relev": [0, 1, 5, 7, 11, 20, 22, 24, 27, 29], "reli": [0, 6, 8], "reliabilti": 22, "reliabl": [7, 24], "relu": [3, 4, 27], "remain": [1, 2, 4, 6, 12, 21, 24, 28, 30], "remaind": 24, "reman": 2, "remark": 1, "rememb": [0, 8, 13, 21, 22, 27], "remind": [0, 5, 11, 13, 21, 24], "remot": 15, "remov": [4, 5, 6, 18, 28, 29, 30], "renam": 15, "render": [0, 27, 28], "reorder": [5, 7, 28, 29], "reorgan": [0, 27], "repeat": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 14, 21, 22, 24, 27, 28, 29, 30], "repeated": 27, "repeatedli": [0, 6, 10, 13], "repet": 3, "repetit": [6, 27, 28], "rephras": [13, 29], "replac": [0, 1, 3, 4, 5, 6, 10, 12, 14, 20, 22, 27, 28, 29], "replica": 6, "repo": [15, 22], "report": [27, 30], "repositori": [4, 22, 27], "repres": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 22, 24, 27, 28, 29, 30], "represent": [0, 1, 3, 6, 24, 27], "representd": 3, "reproduc": [0, 5, 6, 9, 12, 15, 16, 18, 20, 24, 27, 28], "repuls": [0, 27], "request": [0, 13, 30], "requir": [0, 1, 3, 4, 5, 6, 8, 9, 11, 12, 13, 15, 17, 18, 21, 27, 28, 29, 30], "res1": 2, "res2": 2, "res3": 2, "res_analyt": 2, "res_analytical1": 2, "res_analytical2": 2, "res_analytical3": 2, "resaml": 6, "resampl": [0, 7, 10, 20, 27, 28], "rescal": [0, 11, 12, 30], "rescu": 5, "reseach": 6, "research": [0, 4, 13, 20, 26, 27], "resembl": [6, 24], "reserv": [1, 5, 6, 24], "reshap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 21, 27, 28], "residenti": [], "residu": [0, 5, 13, 27], "resiz": [5, 28, 29], "resourc": 27, "respect": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 17, 18, 22, 24, 27, 28, 29, 30], "respond": 12, "respons": [0, 7, 9, 12, 27, 28], "rest": [0, 5, 18, 28, 29, 30], "restat": [0, 12, 27], "restor": 4, "restored_discrimin": 4, "restored_gener": 4, "restrict": [0, 3, 9, 12, 27], "result": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 27, 30], "retail": [], "retain": [5, 6, 28, 29, 30], "return": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 21, 24, 27, 28, 29, 30], "return_data": 14, "return_sequ": 4, "return_x_i": 9, "reus": [1, 3, 6, 19, 22], "reveal": [0, 12, 27], "revers": [1, 21], "review": [20, 21], "revisit": 14, "revolut": 27, "reward": [0, 4, 27], "rewrit": [0, 3, 5, 6, 7, 8, 10, 11, 12, 13, 16, 19, 21, 22, 24, 29, 30], "rewritten": [2, 6, 8, 10, 24], "rewrot": 13, "rf": 10, "rgb": 3, "rgoj5yh7evk": 20, "rh": 6, "rho": [0, 10, 13, 30], "rho_1": 10, "rho_2": 10, "rho_m": 10, "rich": [0, 27], "ride": 9, "rideclass": 9, "ridedata": 9, "ridg": [7, 11, 13, 20, 27], "ridge_paramet": 17, "ridge_sk": 6, "ridgebeta": 29, "ridgetheta": 5, "right": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "right_sid": 2, "rightarrow": [0, 1, 5, 6, 8, 11, 12, 13, 24, 27, 28, 29, 30], "rigor": [0, 27, 28, 29], "ring": 6, "rise": [0, 27], "risk": [0, 13, 27, 29, 30], "rival": 4, "river": [], "rlm": 27, "rm": [24, 30], "rmse": [], "rmsporp": [13, 30], "rmsprop": [1, 3, 4, 13, 22], "rnd_clf": 10, "rng": 24, "rnn": [4, 12], "rnn1": 4, "rnn2": 4, "rnn_2layer": 4, "rnn_input": 4, "rnn_output": 4, "rnn_train": 4, "rntrick1": 24, "rntrick2": 24, "rntrick3": 24, "rntrick4": 24, "ro": [0, 13, 27, 29, 30], "robert": [19, 22, 26], "robust": [0, 27, 30], "robustscal": [0, 28, 30], "roc": [7, 10], "role": [0, 2, 5, 6, 8, 18, 20, 22, 27, 28, 29, 30], "roll": 6, "room": [0, 25, 27], "root": [0, 5, 9, 13, 15, 24, 28, 29, 30], "rot": 27, "rotat": [1, 8, 9, 10], "rotation_matrix": 9, "roughli": [1, 3, 18], "round": [7, 9, 13], "routin": [13, 21, 27, 29], "row": [0, 1, 2, 5, 6, 9, 11, 16, 21, 27, 28, 29], "rr": [5, 28, 29], "rrr": [5, 28, 29], "rudg": [], "rug": [13, 29, 30], "rule": [0, 1, 5, 6, 13, 22, 27, 28, 29], "run": [0, 1, 2, 4, 5, 6, 8, 9, 11, 13, 15, 20, 22, 27, 28, 29, 30], "runtim": [1, 6, 14, 15], "rust": [0, 20, 21, 27], "rvert": 1, "rvert_2": 1, "s_": [3, 6], "s_1": 6, "s_i": [6, 7], "s_j": 6, "s_k": 6, "s_phenomenon": 22, "saddl": [13, 29, 30], "safeguard": [18, 30], "sai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 21, 22, 24, 27, 28, 29], "said": [6, 9, 13, 29], "sake": [0, 5, 7, 11, 27, 28, 29], "sale": [0, 27], "sam": 27, "same": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 18, 21, 22, 24, 27, 28, 29], "samm": 10, "sampl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 14, 18, 19, 20, 21, 22, 24, 27, 28, 30], "sample_vari": 14, "sampleexptvari": 24, "samwis": 27, "sastri": 11, "satisfactori": [0, 27], "satisfi": [1, 2, 3, 6, 8, 13, 21, 24, 29], "satur": [1, 6], "save": [0, 4, 6, 7, 9, 13, 27, 30], "save_fig": [0, 6, 7, 9, 10, 27], "savefig": [0, 4, 6, 7, 9, 24, 27], "savetxt": 4, "saw": [5, 28], "scalabl": 10, "scalar": [2, 5, 6, 10, 28], "scale": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 20, 21, 22, 25, 27, 29], "scale_mean": 4, "scale_std": 4, "scaler": [0, 7, 8, 9, 10, 11, 17, 22, 28], "scan": [5, 7], "scari": 5, "scatter": [0, 1, 6, 7, 8, 9, 14, 15, 17, 27, 28, 30], "scenario": [6, 13, 29, 30], "schedul": [13, 30], "scheme": [1, 13, 29, 30], "schrage": 24, "sch\u00f8yen": [6, 28, 30], "scienc": [0, 1, 10, 12, 13, 20, 23, 24, 25, 26, 29], "scientif": [0, 20, 22, 27], "scientist": [0, 27], "scikit": [3, 5, 6, 8, 9, 10, 13, 15, 16, 20, 21, 22, 26], "scikit_learn": 0, "scikitlearn": 27, "scikitplot": [7, 10], "scipi": [0, 3, 5, 6, 13, 20, 21, 22, 27, 28, 29], "scl": 6, "scm": 15, "score": [0, 1, 3, 6, 7, 9, 10, 11, 15, 16, 22, 25, 27, 28, 30], "scores_kfold": 6, "scratch": [1, 13, 16], "sdg": [13, 30], "sdv4f4s2sb8": [29, 30], "seaborn": [0, 1, 3, 6, 7, 27], "seamless": [0, 20, 22, 27], "search": [0, 1, 3, 5, 9, 13, 15, 27, 29, 30], "sebastian": 27, "sebastianraschka": 27, "sec": 6, "second": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 14, 15, 16, 20, 21, 24, 25, 27, 28, 29], "second_mo": 30, "second_term": 30, "secondeigvector": 11, "secondli": 12, "section": [4, 11, 16, 21, 22, 24, 28, 30], "sector": 0, "see": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 18, 19, 20, 21, 22, 24, 27, 28, 29, 30], "seed": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 18, 24, 27, 28, 29, 30], "seed_imag": 4, "seek": [1, 2, 8], "seem": [1, 3, 4, 30], "seemingli": [0, 27], "seen": [0, 1, 3, 5, 10, 12, 24], "segment": [13, 29], "seismic": 6, "seldomli": [0, 27], "select": [1, 5, 6, 8, 9, 10, 11, 15, 22, 23, 24, 25, 26, 27, 28, 29], "selevet": 15, "self": [1, 5, 28], "sell": 4, "semest": [7, 23], "semi": [8, 13, 29, 30], "semilogx": 6, "send": [5, 12, 13, 25, 27], "senior": [23, 25], "sens": [0, 4, 6, 8, 27], "sensibl": 3, "sensit": [0, 5, 6, 9, 13, 27, 28, 30], "sent": 2, "sentenc": [4, 12], "separ": [0, 1, 2, 4, 6, 8, 9, 12, 14, 18, 20, 22, 24, 27, 30], "septemb": [18, 22, 27], "sequenc": [3, 4, 7, 9, 10, 12, 13, 20, 21, 24, 27, 29], "sequenti": [1, 3, 4, 10, 12, 24], "seri": [0, 1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 21, 27, 28, 29], "serif": [7, 24, 27], "serv": [0, 1, 2, 3, 5, 7, 13, 26, 27, 28, 29, 30], "servic": 22, "session": [1, 15, 22, 23, 25, 27], "set": [1, 4, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 18, 20, 21, 22, 24, 25, 30], "set_major_formatt": 6, "set_major_loc": 6, "set_tick": [1, 8], "set_ticklabel": 1, "set_titl": [0, 1, 2, 3, 7, 12, 14, 27], "set_xlabel": [0, 1, 2, 3, 7, 12, 27], "set_xlim": [7, 12], "set_xticklabel": 1, "set_ylabel": [0, 1, 2, 3, 7, 27], "set_ylim": [7, 12], "set_ytick": 7, "set_yticklabel": [1, 6], "set_zlim": 6, "seth": 4, "setminu": 6, "setosa": [8, 9], "setosa_or_versicolor": 8, "setp": 6, "setup": [1, 4, 6, 8, 20, 27, 28, 29], "sever": [0, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 20, 21, 22, 24, 27, 28, 29, 30], "sgd": [1, 3, 29], "sgd_clf": 8, "sgdclassifi": 8, "sgdreg": 13, "sgdregressor": 13, "sgn": [5, 28, 29], "shallow": [13, 30], "shape": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 21, 27, 28, 29, 30], "share": [1, 3, 15, 27], "shareabl": 15, "she": 7, "shift": [1, 6, 12, 15, 18, 24, 28, 30], "ship": 3, "shire": 27, "short": [4, 5, 22], "shortcom": [13, 29, 30], "shorten": 4, "shorter": 24, "shorthand": 27, "shortli": [21, 27], "should": [0, 2, 3, 5, 6, 8, 9, 11, 12, 15, 18, 21, 22, 24, 27, 28, 30], "show": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 21, 22, 24, 27, 28, 29, 30], "show_shap": 4, "shown": [0, 4, 5, 8, 12, 13, 21, 28, 29, 30], "shrink": [3, 5, 6, 8, 11, 28, 29], "shrinkag": [5, 6, 28, 29], "shrunk": 11, "shuffl": [0, 1, 4, 6, 13, 28, 30], "side": [0, 2, 5, 8, 12, 13, 21, 22, 27, 29], "sigh": [20, 27], "sigma": [0, 1, 5, 6, 7, 10, 11, 12, 13, 19, 21, 22, 24, 27, 28, 29, 30], "sigma0": 24, "sigma1": 24, "sigma2": 24, "sigma_": [5, 21, 27, 28, 29], "sigma_0": [5, 28, 29], "sigma_1": [5, 28, 29], "sigma_2": [5, 28, 29], "sigma_fn": [7, 12], "sigma_i": [0, 5, 27, 28, 29], "sigma_j": [5, 28, 29], "sigma_m": [6, 24], "sigma_n": [11, 24], "sigma_t": 13, "sigma_x": 24, "sigmoid": [1, 2, 4, 7, 8, 10, 12], "sigmundson": [6, 28, 30], "sign": [1, 2, 7, 8, 10, 24, 25], "signal": [1, 3, 10, 12, 30], "signifi": 4, "signific": [1, 30], "significantli": [1, 13, 18, 24, 29, 30], "sim": [4, 5, 6, 13, 19, 24], "similar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 18, 20, 21, 22, 27, 29], "similarli": [0, 1, 3, 5, 8, 10, 13, 24, 27, 28, 29, 30], "simpl": [1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 14, 16, 17, 20, 21, 24], "simplepredict": 10, "simpler": [0, 1, 5, 6, 7, 13, 16, 20, 22, 27, 29, 30], "simplernn": 4, "simplest": [0, 1, 3, 4, 9, 10, 12, 14, 22, 27], "simpletre": 10, "simpli": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 20, 21, 22, 24, 27, 28, 29, 30], "simplic": [2, 5, 6, 7, 8, 9, 10, 11, 12, 14, 28, 29, 30], "simplicti": [5, 28, 29], "simplifi": [0, 6, 9, 18, 20, 22, 27, 28, 30], "simplist": [3, 6, 24], "simul": [6, 18], "simultan": 6, "sin": [0, 1, 2, 3, 4, 9, 12, 13, 21, 27], "sinc": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 16, 18, 21, 22, 24, 26, 27, 28, 29, 30], "sine": [3, 12], "singl": [0, 1, 2, 3, 5, 6, 7, 8, 9, 12, 13, 18, 19, 21, 24, 27, 28, 29, 30], "singular": [0, 6, 13, 21, 27], "sinusoid": 3, "site": [0, 22, 23, 28], "situat": [0, 4, 5, 7, 13, 24, 27, 28, 29, 30], "six": [3, 24], "size": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 18, 21, 22, 24, 27], "sizesp": 30, "sketch": 10, "ski": 9, "skill": 0, "skip": 11, "skl": [0, 6, 27, 28, 30], "sklearn": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 19, 27, 28, 29, 30], "skplt": [7, 10], "sl": [6, 28, 30], "slack": 8, "slice": [2, 21, 27], "slide": [0, 3, 16, 22, 24, 27, 28, 29], "slight": [6, 13], "slightli": [1, 2, 3, 5, 6, 7, 10, 24, 28, 29], "slope": [8, 11, 12], "slow": [0, 2, 8, 13, 18, 28, 29, 30], "slower": [5, 21, 27, 28, 29, 30], "slowest": 21, "slowli": [12, 30], "slp": 1, "small": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 18, 20, 21, 24, 27, 28, 29, 30], "smaller": [0, 1, 2, 5, 6, 8, 9, 11, 13, 24, 27, 28, 29, 30], "smallest": [0, 4, 14, 27], "smallest_row_index": 14, "smooth": [0, 3, 6, 13, 22, 27, 29, 30], "smoother": 30, "sn": [0, 1, 3, 6, 7, 27], "sne": 11, "so": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25, 27, 28, 29, 30], "soar": 6, "social": 0, "soft": [1, 7, 10, 12], "soften": 8, "softmax": [3, 7], "softwar": [0, 8, 20, 21], "sol": 8, "sole": [0, 6, 27], "solid": [0, 7], "solut": [0, 1, 2, 3, 5, 6, 8, 10, 11, 13, 18, 21, 22, 24, 27, 28, 29, 30], "solution_ev": 30, "soluton": 2, "solv": [0, 1, 3, 5, 6, 8, 10, 11, 12, 13, 16, 21, 22, 27, 28], "solve_expdec": 2, "solve_ode_deep_neural_network": 2, "solve_ode_neural_network": 2, "solve_pde_deep_neural_network": 2, "solveod": 2, "solveode_popul": 2, "solver": [2, 7, 8, 9, 10, 21, 27], "some": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 22, 24, 27, 30], "some_model": [6, 28, 30], "somehow": 4, "someon": 16, "someth": [0, 1, 3, 4, 7, 9, 11, 15, 19, 22, 24, 27, 28], "sometim": [0, 1, 11, 12, 13, 14, 28, 30], "soon": [21, 25, 28], "sophist": [0, 27], "sopt": 13, "sort": [5, 6, 9, 11, 24], "sound": [3, 5], "sourc": [0, 1, 3, 6, 20, 21, 22, 24, 27], "space": [0, 1, 4, 5, 8, 9, 11, 12, 13, 14, 24, 28, 29, 30], "span": [0, 3, 5, 9, 11, 21, 27, 28, 29], "spare": 1, "spars": [3, 6, 18, 21, 27, 30], "sparse_mtx": [21, 27], "sparsecategoricalcrossentropi": 3, "sparsiti": [10, 18], "spatial": [1, 2, 3, 12], "speak": 24, "special": [6, 7, 10, 12, 13, 21, 24, 27, 28, 29, 30], "specif": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 15, 16, 20, 21, 22, 24, 26, 27, 28, 29], "specifi": [0, 3, 5, 6, 7, 9, 11, 13, 14, 24, 27, 29, 30], "specifici": [0, 10, 27], "spectacular": 3, "spectral": 1, "speech": [0, 1, 3, 4, 12], "speed": [1, 2, 4, 13, 30], "spend": [16, 24], "spent": 22, "sphere": [0, 28, 30], "spin": 6, "spite": 0, "spline": 8, "split": [1, 3, 4, 5, 6, 8, 9, 10, 11, 14, 16, 17, 22, 24, 27, 29, 30], "splite": 0, "splitter": [1, 10], "spontan": 24, "spot": 3, "spread": [0, 11, 24, 27, 28], "springer": [19, 22, 26, 27], "spuriou": [13, 30], "sqquar": 29, "sqrsignal": 3, "sqrt": [3, 4, 5, 6, 8, 10, 11, 13, 24, 28, 29, 30], "squar": [1, 2, 3, 4, 7, 8, 9, 11, 13, 14, 15, 17, 18, 20, 21, 24], "squarederror": 10, "squaredeuclidean": 14, "squash": 12, "srtm": 6, "srtm_data_norway_1": 6, "stabil": [5, 22, 30], "stabl": [0, 4, 5, 6, 9, 16, 20, 22, 27, 28, 29], "stack": [3, 4], "stage": [5, 13, 15, 22, 30], "stai": [0, 2, 4, 5, 11, 27, 28, 30], "stand": [0, 5, 9, 12, 27, 28, 29], "standard": [0, 1, 4, 5, 6, 7, 8, 10, 12, 17, 18, 21, 22, 24, 27, 29, 30], "standardscal": [0, 6, 7, 8, 9, 10, 11, 17, 28, 30], "stanford": [13, 29], "start": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 21, 24, 25, 27, 28, 29, 30], "start_tim": 14, "stat": 6, "state": [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 20, 24, 27, 28, 29], "statement": [0, 7, 21, 27], "stationari": [29, 30], "statist": [0, 1, 3, 4, 7, 9, 10, 11, 12, 13, 14, 19, 21, 22, 26, 28, 29, 30], "statu": [0, 7, 15, 27], "stavang": 6, "std": [0, 4, 6, 18, 27, 28, 30], "steep": [13, 29, 30], "steepest": 30, "step": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 21, 22, 27, 29], "step_fn": [7, 12], "step_length": [13, 30], "step_siz": 30, "steps_list": 9, "stereo": 3, "still": [0, 2, 3, 5, 6, 11, 13, 24, 28, 29, 30], "stimuli": 12, "stk": [26, 27], "stk2100": [26, 27], "stk3155": [15, 22, 23, 25], "stk4021": [26, 27], "stk4051": [26, 27], "stk4155": [23, 25], "stk5000": 26, "stochast": [0, 1, 5, 6, 8, 11, 12, 29], "stock": 4, "stoke": 12, "stone": [0, 7], "stop": [1, 4, 9, 13, 14, 18, 29], "storag": [5, 28, 29], "store": [0, 1, 2, 3, 6, 11, 13, 24, 27, 30], "storehaug": [25, 27], "str": [1, 3, 4], "straight": [0, 6, 8, 13, 27, 29], "straightforward": [0, 2, 3, 5, 6, 8, 9, 10, 13, 21, 27, 28, 29], "strategi": [0, 1, 9, 27], "stratifi": 6, "strength": [0, 5, 14, 28, 29], "stretch": 11, "strict": [8, 13, 29], "strictli": [8, 13, 29], "stride": [4, 21], "strike": 6, "string": 1, "stroke": 7, "strong": [3, 6, 9, 10, 12, 21, 24], "strongli": [0, 8, 15, 20, 21], "stronli": [], "structur": [0, 1, 2, 3, 6, 9, 10, 12, 20, 27], "stuck": [1, 13, 29, 30], "student": [0, 15, 22, 23, 25, 26, 27], "studi": [0, 3, 4, 5, 6, 7, 8, 11, 12, 13, 20, 22, 26, 27, 28, 29, 30], "studier": 26, "style": [7, 9, 21, 27], "st\u00f8land": 25, "sub": [9, 12, 30], "subdivid": [0, 21, 27], "subfield": 0, "subgradi": 30, "subject": [6, 8, 24], "submit": 27, "subplot": [0, 1, 3, 4, 6, 7, 8, 9, 10, 14, 27], "subplots_adjust": [8, 24], "subprogram": [21, 27], "subract": [0, 28], "subroutin": [0, 27], "subscript": 1, "subsequ": [1, 4, 5, 6, 12, 21, 24, 28, 29], "subset": [1, 6, 9, 12, 13, 20, 27, 29, 30], "subspac": [0, 8, 11, 28], "substanti": [9, 10], "substep": 11, "substitut": [3, 6, 12, 16, 21], "subsubset": 9, "subtask": 6, "subtl": 1, "subtract": [0, 4, 5, 6, 11, 13, 18, 21, 22, 24, 28, 30], "subtre": 9, "succeed": [0, 4, 27], "success": [3, 7, 9, 13, 24], "successfulli": [4, 9], "sudo": [0, 20, 22, 27], "suffer": [0, 1, 2, 5, 10, 27, 28, 29], "suffici": [1, 6, 8, 11, 13, 29], "suggest": [1, 13, 22, 26, 29, 30], "suit": [8, 12], "suitabl": [0, 15, 19, 24, 28], "sum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 19, 21, 24, 27, 28, 29, 30], "sum_": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 19, 21, 22, 24, 27, 28, 29, 30], "sum_i": [0, 2, 5, 6, 8, 13, 19, 22, 28, 29, 30], "sum_j": [6, 18, 30], "sum_ja_": 0, "sum_k": [6, 8, 12, 21], "sum_logist": 13, "sum_m": 3, "sum_n": 3, "sum_nx_": 3, "summar": [5, 6, 9], "summari": [1, 3, 4, 10, 23, 29], "summat": [0, 3, 16, 28, 29], "sunni": 9, "super": [5, 28, 29], "superfici": 3, "superscript": [1, 12], "supervis": [0, 5, 6, 7, 9, 12, 20, 27, 28, 29], "supplement": [7, 22], "support": [0, 1, 9, 10, 11, 13, 20, 27, 28], "suppos": [0, 5, 6, 7, 8, 10, 11, 12, 13, 21, 27, 28, 29, 30], "suppress": [5, 13, 29], "sure": [0, 1, 4, 6, 16, 22], "surf": 6, "surfac": [0, 6, 27], "surpass": 6, "surpris": [0, 27], "surround": [3, 20], "survei": [0, 5, 6, 27, 28], "svc": [8, 9, 10], "svd": [0, 6, 11, 27], "svdinv": 5, "svm": [8, 9, 10, 11], "svm_clf": [8, 10], "swath": [5, 28, 29], "switch": 0, "sy": [13, 29, 30], "symbol": [1, 5, 11, 13, 20, 24, 27, 28, 29], "symmeteri": 1, "symmetr": [0, 5, 8, 11, 12, 13, 21, 27, 28], "symmetri": 6, "sympi": [0, 20, 22, 27], "synonim": 24, "syntax": 13, "system": [0, 1, 3, 4, 6, 7, 9, 10, 12, 13, 15, 20, 21, 22, 27, 29], "systemat": [4, 6], "t": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 27, 29, 30], "t0": [3, 6, 13, 30], "t1": [2, 13, 30], "t2": 2, "t3": 2, "t_": 2, "t_0": [2, 9, 13, 30], "t_1": [13, 30], "t_b": 10, "t_i": [1, 2, 5, 12, 28, 29], "t_j": 12, "t_k": 9, "tabl": [9, 22, 24, 25, 27], "tabul": [0, 27], "tabular": 27, "tackl": 4, "tag": [2, 3, 4, 5, 6, 7, 12, 13, 14, 21, 24, 28, 29], "taht": [0, 27], "tail": 24, "tailor": [2, 8, 11, 27], "taiwan": [0, 27], "take": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 20, 21, 24, 27, 28, 29, 30], "taken": [0, 1, 3, 6, 10, 13, 21], "tan": 3, "tangent": [1, 4, 12, 13, 29], "tanh": [1, 4, 7, 8, 12], "target": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 18, 19, 27, 28, 29, 30], "target_nam": 9, "task": [0, 1, 3, 6, 9, 11, 12, 14, 22, 27], "tau": [3, 5, 24], "taught": 27, "tax": [], "taylor": [2, 13, 29], "taylornr": [13, 29], "tc": 8, "teach": [15, 23, 27], "team": 1, "teaser": 0, "technic": [0, 5, 6, 13, 22, 29, 30], "techniqu": [0, 1, 8, 10, 13, 20, 24, 26, 27, 28, 30], "technologi": [0, 1], "tell": [0, 4, 6, 10, 11, 13, 16, 24, 30], "temp": 1, "temp1": 1, "temp2": 1, "temperatur": [0, 9, 27], "templat": 18, "temporarili": 1, "ten": [3, 27], "tend": [3, 5, 6, 8, 9, 10, 12, 13, 14, 28, 30], "tendenc": [0, 27], "tension": 6, "tensor": 3, "tensorflow": [0, 2, 4, 8, 14, 20, 21, 22, 26, 27, 28], "term": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 22, 24, 27, 28, 29, 30], "term1": [5, 6, 11], "term2": [5, 6, 11], "term3": [5, 6, 11], "term4": [5, 6, 11], "termin": [0, 4, 5, 9, 10, 13, 15, 28, 29, 30], "terminarl": 15, "terrain": 6, "terrain1": 6, "test": [3, 4, 5, 6, 7, 8, 9, 10, 13, 16, 21, 22, 24, 27, 29, 30], "test_acc": 3, "test_accuraci": [1, 3], "test_error": 6, "test_imag": [3, 4], "test_ind": 6, "test_input": 4, "test_label": [3, 4], "test_loss": 3, "test_pr": 1, "test_predict": 1, "test_rnn": 4, "test_scor": [7, 10], "test_siz": [0, 1, 3, 5, 6, 10, 15, 17, 28, 29, 30], "test_split": 9, "testerror": [0, 6, 28], "testi": 4, "testpredict": 4, "testx": 4, "text": [0, 1, 2, 4, 5, 8, 9, 11, 13, 15, 18, 21, 24, 26, 28, 29, 30], "textbf": [], "textbook": [16, 22, 28, 29], "textual": 9, "textur": 1, "tf": [1, 3, 4, 13, 14, 29], "th": [0, 1, 2, 5, 6, 7, 9, 12, 13, 14, 21, 22, 24, 27, 28, 30], "than": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 17, 20, 24, 27, 28, 30], "thank": [4, 6, 28, 30], "theano": [1, 20, 27], "thei": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 18, 21, 22, 24, 27, 28, 29, 30], "them": [0, 1, 3, 4, 6, 8, 9, 10, 11, 12, 13, 18, 19, 21, 22, 27, 28], "theme": [0, 15, 27], "themselv": [0, 22, 24, 27], "thenc": 6, "theorem": [2, 6, 7, 28, 29], "theoret": [0, 4, 10], "theori": [0, 1, 3, 8, 9, 12, 13, 19, 20, 22, 26, 27], "thereaft": [0, 5, 6, 11, 12, 21, 22, 27], "therebi": [0, 5, 7, 11, 22, 27, 28, 29], "therefor": [0, 1, 2, 3, 4, 6, 7, 8, 11, 13, 19, 24, 27, 28, 29, 30], "therein": 11, "thereof": [0, 6, 13, 27, 30], "theta": [0, 1, 4, 5, 6, 7, 13, 16, 22, 24, 27, 28, 29, 30], "theta1": 30, "theta2": 30, "theta_": [0, 1, 6, 7, 13, 27, 28, 29, 30], "theta_0": [0, 5, 6, 7, 16, 27, 28, 29, 30], "theta_0x_": [0, 27, 28], "theta_1": [0, 5, 6, 7, 27, 28, 29, 30], "theta_1x_": [0, 27, 28], "theta_1x_0": [0, 27], "theta_1x_1": [0, 7, 27], "theta_1x_2": [0, 27], "theta_1x_i": [7, 28, 29, 30], "theta_2": [0, 27, 28], "theta_2x_": [0, 27, 28], "theta_2x_0": [0, 27], "theta_2x_1": [0, 27], "theta_2x_2": [0, 7, 27], "theta_2x_i": 28, "theta_3x_i": 28, "theta_4x_i": 28, "theta_closed_form": 18, "theta_closed_formol": 18, "theta_closed_formridg": 18, "theta_gdol": 18, "theta_gdridg": 18, "theta_i": [0, 1, 5, 27, 28, 29], "theta_j": [0, 5, 6, 18, 27, 28, 30], "theta_k": [29, 30], "theta_linreg": [13, 29, 30], "theta_ol": 18, "theta_p": 7, "theta_px_p": 7, "theta_ridg": 18, "theta_t": [13, 30], "theta_tru": 18, "thetavalu": 5, "thi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 28, 29, 30], "thing": [0, 1, 2, 4, 5, 7, 9, 15, 16, 18, 24, 27], "think": [0, 1, 3, 4, 6, 9, 12, 13, 14, 24, 27, 28, 29, 30], "third": [0, 3, 6, 13, 25, 27, 29, 30], "thirti": 7, "thorughout": 27, "those": [0, 3, 5, 6, 8, 9, 10, 11, 21, 22, 27, 28, 29, 30], "though": [1, 2, 3, 4, 13, 16, 17, 21, 24, 30], "thought": [6, 14, 22, 24], "thousand": [0, 1, 22, 28, 30], "three": [0, 1, 3, 5, 6, 8, 9, 12, 21, 22, 23, 24, 25, 27, 28, 29], "threshold": [1, 3, 9, 10, 11, 12, 13, 30], "through": [0, 1, 2, 3, 4, 5, 6, 8, 11, 12, 13, 14, 15, 20, 21, 22, 24, 27, 28, 29, 30], "throughout": [0, 4, 5, 14, 15, 20, 21, 24, 27], "throw": [3, 6, 24], "thu": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 25, 27, 28, 29, 30], "thumb": [0, 6, 22, 28], "thursdai": [], "tibshirani": [6, 19, 22, 26, 27], "tick_param": 6, "ticker": [6, 13, 24, 29, 30], "tif": 6, "tight_layout": [1, 7], "tightli": 11, "tild": [0, 5, 6, 7, 11, 19, 22, 24, 27, 28, 29, 30], "till": [0, 4, 7, 8, 9, 10, 12, 21, 27, 28], "time": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 27, 28, 29], "timeit": 4, "timer": 4, "tini": 1, "tip": 3, "titl": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 15, 24, 27, 29, 30], "tmp": 13, "tn": [2, 3, 7], "to_categor": [1, 3, 4], "to_categorical_numpi": 1, "to_numer": [0, 6, 27], "todai": 3, "togeth": [0, 3, 6, 8, 11, 13, 20, 27], "toi": 14, "told": 13, "toler": [2, 14], "tolist": 4, "tomographi": 12, "too": [0, 2, 4, 5, 6, 9, 11, 13, 17, 18, 24, 26, 28, 29, 30], "took": [8, 27], "tool": [0, 1, 3, 6, 13, 15, 20, 28], "toolbox": 8, "top": [0, 3, 5, 6, 9, 10, 19, 20, 27], "topic": [0, 5, 6, 7, 8, 20, 22, 28, 29], "topolog": [3, 12], "topologi": [1, 12], "torkjellsdatt": [25, 27], "toss": [10, 24], "total": [0, 1, 2, 3, 4, 6, 7, 8, 10, 11, 12, 13, 14, 21, 24, 25, 27, 28, 29, 30], "total_loss": 4, "totalclustervari": 14, "totalscatt": 14, "toward": [1, 2, 7, 12, 13, 15, 29], "towardsdatasci": 30, "town": [], "tp": [4, 7], "tpng": 9, "tpu": [13, 20, 27], "tqdm": 6, "tr": [], "track": [3, 13, 14, 15, 21, 28, 29, 30], "tract": [], "tractabl": [0, 27, 28], "trade": [5, 9], "tradeoff": [0, 5, 19, 22, 27, 28, 29], "tradit": [0, 1, 4, 6, 27], "train": [2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 16, 17, 22, 29, 30], "train_accuraci": [0, 1, 3, 27], "train_dataset": 4, "train_end": [0, 1, 28], "train_error": 6, "train_imag": [3, 4], "train_ind": 6, "train_label": [3, 4], "train_pr": 1, "train_siz": [0, 1, 3, 28], "train_step": 4, "train_test_split": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "train_test_split_numpi": [0, 1, 28], "trainable_vari": 4, "trained_model": [6, 28, 30], "trainerror": [0, 28], "traini": 4, "training_checkpoint": 4, "training_dataset": 4, "training_gradi": [13, 30], "trainingerror": 6, "trainpredict": 4, "trainscor": 4, "trainx": 4, "trait": [0, 27], "trajectori": 4, "transfer": [9, 27], "transform": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 20, 21, 27, 28, 29, 30], "transit": [6, 12], "translat": [1, 4, 6, 10, 27, 28, 30], "transpos": [1, 5, 11, 21, 28, 29], "travers": [0, 5], "treat": [0, 1, 3, 6, 12, 13, 18, 24, 27, 28, 29, 30], "tree": [0, 1, 20, 27], "tree_clf": [9, 10], "tree_clf_": 9, "tree_clf_sr": 9, "tree_reg": 9, "tree_reg1": 9, "tree_reg2": 9, "trend": 24, "treue": 7, "trevor": [19, 22, 26], "tri": [2, 3, 4, 9, 13, 16], "triain": 0, "trial": [0, 2, 4, 6, 13, 24, 27, 29, 30], "triangl": [13, 29], "triangular": 21, "trick": [3, 4, 8, 11, 13, 24, 30], "trickier": 24, "tridiagon": 21, "trillion": 20, "trivial": [0, 1, 5, 11, 24, 27, 29], "troubl": [0, 8, 12, 15, 28, 30], "truck": 3, "true": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "true_beta": 28, "true_fun": 6, "true_theta": [6, 30], "truli": 27, "try": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 18, 20, 21, 22, 24, 27, 28, 29, 30], "tucker": 8, "tuesdai": [25, 27], "tumor": [7, 9], "tumour": 7, "tunabl": 1, "tune": [4, 9, 13, 21, 27, 30], "turn": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 24, 27, 28, 29, 30], "tutori": [1, 4], "tv": 2, "tveito": 2, "tweak": [1, 4, 10, 24], "twice": [13, 29], "twist": 11, "two": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 17, 21, 22, 23, 24, 26, 27, 28, 29, 30], "tx": [13, 29, 30], "tx_1": [13, 29], "txt": [4, 15], "ty": [13, 29], "type": [0, 1, 3, 6, 8, 10, 13, 21, 24, 28, 29, 30], "typic": [0, 1, 2, 3, 4, 5, 7, 9, 10, 12, 13, 15, 16, 24, 27, 28, 29, 30], "typo": 22, "u": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 21, 22, 24, 26, 27, 28, 29, 30], "u_": 21, "u_i": 12, "u_m": 10, "ua": [0, 27], "ubuntu": [0, 20, 22, 27], "uci": 22, "uio": [15, 22, 25, 26], "un": 14, "unabl": 15, "unari": [21, 27], "unbalanc": [6, 9], "unbias": [0, 5, 6, 27], "uncent": [6, 28, 30], "uncertainti": [0, 5, 27], "uncertitud": 24, "unchang": [1, 3], "uncorrel": [10, 24], "undefin": [5, 28, 29], "under": [0, 1, 5, 6, 10, 13, 20, 22, 27, 28, 29], "underdetermin": [0, 27], "underfit": [1, 6], "underflowproblem": 5, "undergo": 5, "undergradu": [23, 25], "underli": [0, 1, 9, 13, 18, 24, 27, 30], "underset": [4, 14], "understand": [0, 1, 3, 5, 6, 10, 13, 14, 15, 20, 27, 28, 29, 30], "understood": [8, 13], "undesir": 8, "undetermin": [5, 8], "undo": 4, "unexpect": 6, "unexpected": 24, "unexplain": 18, "unfair": [6, 28], "unfortun": [1, 8, 9, 10], "unicode_liter": [8, 9], "uniform": [0, 1, 5, 6, 11, 13, 22, 24, 27, 29, 30], "uniformli": [13, 24, 29, 30], "unifrompdf": 24, "unimport": [13, 29], "union": [5, 6], "uniqu": [0, 2, 6, 13, 14, 21, 27], "unique_cluster_label": 14, "unit": [0, 1, 3, 4, 5, 10, 12, 18, 24, 27, 28, 29, 30], "unitari": [5, 6, 21, 28, 29], "unitarili": [21, 27], "uniti": 24, "univari": 24, "univers": [0, 1, 2, 13, 20, 22, 23, 25, 27, 28, 29, 30], "unix": 1, "unknow": [0, 21, 27], "unknown": [0, 1, 3, 4, 5, 6, 8, 10, 13, 21, 22, 27, 28, 29, 30], "unknowwn": 12, "unlabel": 1, "unless": [0, 3, 6, 11, 13, 22, 27, 29], "unlik": [1, 3, 8, 13, 29, 30], "unnecessarili": 9, "unord": 3, "unpublish": 30, "unravel": 1, "unrol": [3, 11], "unseen": [0, 7, 9, 15], "unstabl": 1, "unsupervis": [0, 1, 4, 12, 20, 27], "unsymmetr": [21, 27], "until": [1, 2, 4, 9, 12, 13, 14, 29], "untouch": 0, "unusu": 12, "up": [1, 3, 4, 5, 6, 8, 10, 11, 13, 14, 16, 18, 19, 20, 21, 22, 24, 25, 30], "updat": [1, 2, 10, 12, 13, 14, 15, 18], "uploa": 27, "upload": [15, 20, 22, 26], "upon": [0, 1, 6, 7, 11, 21], "upper": [0, 8, 9, 16, 21, 28], "uppercas": [21, 27], "upsampl": 4, "upscal": 4, "url": [27, 28], "us": [4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 17, 19, 21, 24, 26], "usag": [0, 8, 20, 27, 28, 30], "usd": [], "usd10000": [], "use_bia": 4, "usecol": [0, 27], "useless": 1, "user": [0, 1, 2, 4, 6, 7, 15, 20, 21, 22, 27, 28], "usernam": [15, 22], "usetex": 24, "usg": 6, "usr": 24, "usual": [0, 3, 4, 7, 12, 13, 14, 27, 30], "ut": 5, "util": [1, 3, 4, 6, 7, 10, 14, 19, 27], "ux": 21, "v": [2, 4, 5, 6, 11, 13, 15, 20, 28, 29], "v0": 24, "v1": 24, "v2": 24, "v_": 30, "v_0": [11, 30], "v_t": 30, "va": 1, "vahid": 27, "val": 13, "val_accuraci": 3, "val_loss": 4, "vale": 2, "valid": [0, 1, 4, 7, 9, 10, 13, 20, 24, 27, 28, 30], "validation_data": 3, "validation_split": 4, "valu": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 20, 21, 22, 27, 30], "valuat": 9, "valy": 4, "van": [0, 19, 22, 27, 28, 29, 30], "vandenbergh": [8, 13, 29], "vandermond": [0, 27], "vanilla": [0, 6, 11, 14, 28, 30], "vanish": [1, 4, 13, 24, 29], "var": [5, 6, 10, 11, 19, 22, 24, 28], "var_x": 24, "varabl": 8, "varepsilon": [5, 6, 19], "varepsilon_": [5, 6], "varepsilon_i": [5, 6], "vari": [0, 1, 3, 5, 6, 10, 27], "variabl": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 14, 21, 27, 28, 30], "varianc": [0, 1, 5, 7, 9, 10, 11, 13, 14, 18, 20, 21, 24, 27, 28, 29, 30], "variance_i": [5, 11, 28], "variance_x": [5, 11, 28], "variant": [0, 1, 6, 8, 12, 13, 27, 28, 29, 30], "variat": [3, 4, 11, 27], "varieti": [0, 3, 12, 20, 22, 27], "variou": [1, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 19, 20, 21, 22, 24, 27, 28, 29, 30], "varydimens": 4, "vastli": 3, "vaue": 1, "vault": 0, "vdot": [2, 13, 29, 30], "ve": [22, 30], "vec": 6, "vector": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 17, 18, 20, 29, 30], "vector_mean": 14, "ventur": [0, 8, 20, 27], "venv": 15, "verbos": [1, 3, 4], "veri": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 22, 24, 26, 27, 28, 29, 30], "verifi": [3, 11, 21, 27], "versatil": [8, 27], "versicolor": [8, 9], "version": [0, 3, 10, 13, 14, 15, 20, 21, 22, 24, 27], "versu": 1, "vert": [0, 1, 5, 6, 7, 8, 9, 11, 13, 16, 17, 27, 28, 29, 30], "vert_1": [5, 6, 28, 29, 30], "vert_2": [5, 6, 11, 17, 28, 29, 30], "via": [0, 5, 6, 7, 8, 9, 10, 11, 12, 19, 20, 21, 22, 23, 24, 25, 27, 28, 29, 30], "vidal": 11, "video": [0, 1, 12, 20, 23, 25, 27, 28, 29], "view": [1, 3, 5, 6, 12, 13, 24, 26, 27, 29, 30], "violat": 8, "virginica": 9, "viridi": [0, 1, 2, 3, 27], "virtual": 1, "viscos": 13, "viscou": 13, "visibl": 15, "vision": [0, 3], "visual": [0, 3, 11, 12, 18, 20, 27, 28], "visualis": 1, "visualstudio": [15, 16], "viz": [6, 8, 24], "vmap": 13, "vmax": [1, 6], "vmh0zpt0tli": 30, "vmin": [1, 6], "voic": 3, "volatil": 30, "volum": [0, 3, 27], "vote": [10, 27], "voting_clf": 10, "votingclassifi": 10, "votingsimpl": 10, "vstack": [5, 11, 21, 24, 27, 28], "vt": [5, 28, 29], "w": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 21, 24, 27, 28, 29, 30], "w1": 8, "w2": [8, 11], "w3": 8, "w_": [1, 12], "w_1": [8, 21], "w_1x_": 8, "w_1x_1": 8, "w_2": [8, 21], "w_2x_": 8, "w_2x_2": 8, "w_3": 21, "w_4": 21, "w_hidden": 2, "w_i": [1, 2, 10], "w_ix_i": 12, "w_j": 21, "w_m": 21, "w_output": 2, "w_px_": 8, "w_px_p": 8, "w_t": [], "wa": [1, 3, 4, 5, 6, 7, 10, 11, 12, 14, 17, 21, 27, 28, 30], "wai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 18, 19, 21, 24, 27, 28, 29, 30], "walk": 9, "walker": 24, "wang": [0, 27], "want": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 20, 22, 24, 27, 28, 29, 30], "warn": 4, "warrant": 6, "wast": [3, 30], "watch": [20, 29, 30], "wave": 3, "wavelet": 8, "we": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29], "weak": [9, 10, 14], "weather": [1, 12], "web": [20, 23, 25, 27], "webpag": 27, "websit": [6, 21, 22, 23, 27], "wedg": [8, 24], "wednesdai": [25, 27], "wee": 11, "week": [0, 5, 6, 7, 22, 23, 25], "weekli": [15, 16, 20, 22, 23, 25, 26, 27], "weight": [1, 2, 3, 6, 7, 9, 10, 12, 13, 18, 24, 30], "weigth": 2, "welcom": [8, 15, 20], "well": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 20, 21, 22, 24, 26, 27, 28, 29, 30], "went": 8, "were": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 24, 27], "wessel": [0, 19, 22, 27, 28, 29, 30], "what": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 24, 30], "whatev": 3, "when": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 24, 27, 28, 29], "whenev": [13, 15, 24, 30], "where": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 25, 27, 28, 29, 30], "wherea": [6, 24, 30], "wherefrom": 22, "wherein": [1, 12], "whether": [0, 3, 5, 7, 9, 22, 24, 27], "which": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 29], "whichev": [1, 3], "while": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 19, 24, 27, 28, 29], "white": 9, "whiteboad": 30, "whiteboard": [28, 29], "who": [0, 15], "whole": [1, 3, 4, 5, 9, 11, 13, 30], "whose": [0, 6, 10, 24, 28], "whow": [11, 28], "why": [0, 1, 3, 6, 13, 15, 16, 17, 19, 22, 28, 29], "wide": [0, 1, 3, 6, 7, 12, 20, 21, 22, 27], "widehat": 6, "width": [0, 3, 8, 9, 27], "wieringen": [0, 19, 22, 27, 28, 29, 30], "wiki": 22, "wikipedia": 22, "win": 10, "wind": 9, "wing": [25, 27], "winther": 2, "wiothout": 6, "wiscons": 7, "wisconsin": 10, "wisdom": [6, 28, 30], "wise": [1, 5, 12, 13, 28, 29, 30], "wish": [0, 2, 5, 7, 8, 11, 13, 14, 18, 21, 22, 27, 28, 29, 30], "with_std": [0, 28], "wither": 6, "within": [0, 2, 3, 4, 7, 9, 12, 13, 14, 24, 26, 27, 29], "withinclust": 14, "without": [0, 1, 5, 6, 8, 9, 11, 12, 13, 15, 18, 22, 27, 28, 29, 30], "won": [0, 15, 27], "wonder": 8, "word": [0, 1, 3, 4, 5, 6, 7, 14, 24, 27, 28, 29, 30], "work": [0, 1, 4, 6, 7, 8, 9, 13, 15, 16, 18, 20, 22, 23, 24, 25, 27, 28, 30], "workabl": 30, "workshop": 27, "world": [0, 8, 16, 28], "worldwid": [0, 27], "worri": 15, "wors": [0, 1, 3, 4, 6, 27], "worth": 9, "worthi": 22, "would": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 18, 21, 22, 24, 27, 28, 29, 30], "wrap": [6, 21, 27], "write": [0, 1, 2, 3, 5, 6, 7, 8, 12, 13, 15, 16, 18, 21, 27, 28, 30], "written": [0, 2, 3, 5, 11, 12, 13, 16, 20, 21, 22, 24, 27, 28, 29, 30], "wrong": [1, 8, 15], "wrongli": 10, "wrote": [5, 11, 28], "wrt": [10, 13, 30], "wth": [10, 13, 30], "www": [20, 21, 22, 26, 27, 29, 30], "wx_1": 8, "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 27, 29, 30], "x0": 8, "x1": [4, 8, 9, 10, 13], "x1_exampl": 8, "x1d": 8, "x2": [8, 9, 10, 13], "x2d": [8, 11], "x2d_train": 11, "x2dsl": 11, "x3": 8, "x_": [0, 2, 3, 5, 6, 8, 10, 11, 13, 14, 21, 24, 27, 28, 29, 30], "x_0": [0, 5, 11, 18, 21, 27, 28], "x_1": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 18, 21, 24, 27, 28, 29, 30], "x_2": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 21, 24, 27, 28, 29], "x_3": [8, 21, 24], "x_4": 21, "x_6": 18, "x_center": 11, "x_data": 1, "x_data_ful": 1, "x_hidden": 2, "x_i": [0, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 24, 27, 28, 29, 30], "x_input": 2, "x_ix_": [0, 27], "x_iy_i": 8, "x_j": [0, 2, 8, 9, 12, 16, 24, 28, 30], "x_jy_j": 8, "x_k": [12, 14, 21, 24, 28], "x_l": 24, "x_m": [6, 12, 21, 24], "x_mean": [18, 30], "x_n": [0, 2, 3, 6, 8, 11, 12, 13, 21, 24, 27, 29], "x_new": [9, 10], "x_norm": [18, 30], "x_offset": [6, 28, 30], "x_output": 2, "x_p": [3, 7, 9], "x_poli": 9, "x_poly10": 9, "x_pred": 4, "x_prev": 2, "x_reduc": 11, "x_sampl": 19, "x_scale": 8, "x_small": 13, "x_std": [18, 30], "x_t": 30, "x_test": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30], "x_test_": 17, "x_test_own": 6, "x_test_scal": [0, 6, 7, 9, 10, 11, 28, 30], "x_tot": 4, "x_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "x_train_": 17, "x_train_mean": [6, 28, 30], "x_train_own": 6, "x_train_scal": [0, 6, 7, 9, 10, 11, 28, 30], "x_val": 1, "xarrai": [20, 27], "xavier": 1, "xbnew": [13, 29, 30], "xcode": [0, 20, 22, 27], "xdclassiffierconfus": 10, "xdclassiffierroc": 10, "xg_clf": 10, "xgb": 10, "xgbclassifi": 10, "xgboost": 9, "xgboot": 10, "xgbregressor": 10, "xgparam": 10, "xgtree": 10, "xi": [8, 13, 30], "xi_": 8, "xi_1": 8, "xi_i": 8, "xk": 8, "xla": [13, 20, 27], "xlabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 24, 27, 28, 29, 30], "xlim": [6, 10], "xm": 9, "xmesh": 13, "xnew": [0, 13, 27, 29, 30], "xp": 24, "xpanda": [0, 28], "xpd": [5, 11, 28], "xplot": 0, "xscale": [0, 28], "xsr": 9, "xt_x": [13, 29, 30], "xtest": 6, "xtick": [3, 6, 8, 9], "xtrain": 6, "xu": [0, 27], "xx": [0, 21, 27], "xy": [0, 6, 8, 21, 27], "xytext": 8, "xz": [21, 27], "y": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "y1": 4, "y2": 4, "y3": 4, "y_": [0, 1, 5, 6, 10, 11, 21, 27, 28], "y_0": [0, 5, 11, 21, 27, 28], "y_1": [0, 5, 8, 9, 11, 13, 21, 27, 28, 29, 30], "y_1y_1": 8, "y_1y_1k": 8, "y_1y_2": 8, "y_1y_2k": 8, "y_1y_n": 8, "y_1y_nk": 8, "y_2": [0, 5, 8, 9, 11, 21, 27, 28], "y_2y_1": 8, "y_2y_1k": 8, "y_2y_2": 8, "y_2y_2k": 8, "y_3": [0, 9, 21], "y_4": 21, "y_center": [18, 30], "y_data": [0, 1, 5, 6, 27, 28, 29, 30], "y_data_ful": 1, "y_decis": 8, "y_fit": [0, 28], "y_i": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 19, 21, 22, 27, 28, 29, 30], "y_if_": 10, "y_ix_": [0, 27], "y_ix_i": [7, 8, 13, 28, 29, 30], "y_iy_jk": 8, "y_j": [6, 8, 12, 22], "y_k": 12, "y_m": 21, "y_mean": [18, 30], "y_model": [0, 4, 5, 6, 27, 28, 29, 30], "y_n": [8, 13, 29, 30], "y_ny_1": 8, "y_ny_1k": 8, "y_ny_2": 8, "y_ny_2k": 8, "y_ny_n": 8, "y_ny_nk": 8, "y_offset": [6, 17, 28, 30], "y_plot": 9, "y_pred": [0, 1, 4, 6, 7, 8, 9, 10, 28, 30], "y_pred1": 9, "y_pred2": 9, "y_pred_rf": 10, "y_pred_tre": 10, "y_proba": [7, 10], "y_sampl": 19, "y_scaler": [6, 28, 30], "y_test": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30], "y_test_onehot": 1, "y_test_predict": [], "y_tot": 4, "y_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 27, 28, 29, 30], "y_train_mean": [6, 28, 30], "y_train_onehot": 1, "y_train_predict": [], "y_train_scal": [6, 28, 30], "y_val": 1, "ye": [3, 6, 7], "year": [0, 20, 27], "yet": [0, 1, 6, 8, 11, 13, 27], "yi": [13, 30], "yield": [0, 2, 5, 6, 8, 10, 12, 13, 14, 21, 24, 27, 29, 30], "yk": 8, "ylabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 24, 27, 28, 29, 30], "ylim": [3, 6], "ym": 9, "ymesh": 13, "yn": 0, "yo": [8, 9, 10], "yoshua": [1, 26], "you": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30], "young": 0, "your": [1, 2, 4, 5, 6, 8, 11, 13, 15, 17, 19, 20, 21, 27, 29, 30], "your_model_object": 16, "yourself": [11, 13, 27, 29], "youtu": [28, 29], "youtub": [20, 29, 30], "ypred": 6, "ypredict": [0, 13, 27, 28, 29, 30], "ypredict2": [13, 29, 30], "ypredictlasso": [5, 29], "ypredictol": [0, 5, 29], "ypredictown": [6, 28, 30], "ypredictownridg": [6, 28, 29, 30], "ypredictridg": [0, 5, 6, 28, 29, 30], "ypredictskl": [6, 28, 30], "ytest": 6, "ytick": [3, 6, 8, 9], "ytild": [0, 6, 27, 28], "ytildelasso": [5, 29], "ytildenp": [0, 27, 28], "ytildeol": [0, 5, 29], "ytildeownridg": [6, 28, 29, 30], "ytilderidg": [5, 6, 28, 29, 30], "ytrain": 6, "yuxi": 27, "yx": [21, 27], "yy": [21, 27], "yz": [21, 27], "z": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 21, 24, 27, 28], "z_": [1, 2, 12, 21, 27], "z_0": [21, 27], "z_1": [21, 27], "z_2": [21, 27], "z_c": 1, "z_h": 1, "z_hidden": 2, "z_i": [1, 12], "z_j": [1, 12], "z_k": [12, 28], "z_m": 1, "z_mod": 9, "z_o": 1, "z_output": 2, "zaman": 24, "zaxi": 6, "zero": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 27, 28, 29, 30], "zeros_lik": 4, "zeroth": 28, "zfill": 4, "zip": [4, 6], "zm_h": [0, 27], "zn": [], "zone": [], "zoom": 27, "zx": [21, 27], "zy": [21, 27], "zz": [21, 27], "\u00f8yvind": [6, 28, 30]}, "titles": ["3. Linear Regression", "14. Building a Feed Forward Neural Network", "15. Solving Differential Equations with Deep Learning", "16. Convolutional Neural Networks", "17. Recurrent neural networks: Overarching view", "4. Ridge and Lasso Regression", "5. Resampling Methods", "6. Logistic Regression", "8. Support Vector Machines, overarching aims", "9. Decision trees, overarching aims", "10. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods", "11. Basic ideas of the Principal Component Analysis (PCA)", "13. Neural networks", "7. Optimization, the central part of any Machine Learning algortithm", "12. Clustering and Unsupervised Learning", "Exercises week 34", "Exercises week 35", "Exercises week 36", "Exercises week 37", "Exercises week 38", "Applied Data Analysis and Machine Learning", "2. Linear Algebra, Handling of Arrays and more Python Features", "Project 1 on Machine Learning, deadline October 6 (midnight), 2025", "Course setting", "1. Elements of Probability Theory and Statistical Data Analysis", "Teachers and Grading", "Textbooks", "Week 34: Introduction to the course, Logistics and Practicalities", "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression", "Week 36: Linear Regression and Gradient descent", "Week 37: Gradient descent methods"], "titleterms": {"": [8, 10, 29, 30], "1": [0, 15, 16, 17, 18, 19, 22, 28], "15": 19, "19": 19, "1a": 18, "2": [0, 15, 16, 17, 18, 19, 27, 28, 29], "2023": 25, "2025": 22, "2a": [], "2b": [], "3": [0, 15, 16, 17, 18, 19, 28], "34": [15, 27], "35": [16, 28], "36": [17, 29], "37": [18, 30], "38": 19, "3a": 18, "3b": 18, "4": [0, 15, 16, 17, 18, 19, 28], "4a": 18, "4b": 18, "5": [0, 16, 18], "6": 22, "8": 30, "A": [0, 1, 4, 8, 9, 27], "And": [27, 28, 30], "But": 30, "In": 25, "Ising": 6, "The": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 15, 20, 27, 28, 29, 30], "To": 27, "With": [4, 29], "about": [27, 28, 29], "abov": 29, "accuraci": 30, "across": 30, "activ": [1, 12], "ad": [0, 6, 22, 27, 28], "adaboost": 10, "adagrad": [13, 30], "adam": [13, 30], "adapt": [10, 30], "adjust": 1, "advanc": 22, "adversari": 4, "again": [3, 9], "ai": [22, 27], "aim": [8, 9, 27], "aka": 27, "al": 30, "algebra": [21, 27], "algorithm": [9, 10, 11, 12, 27, 28, 29, 30], "algortithm": [13, 29], "all": 8, "an": [0, 4, 10, 15, 27], "analys": [5, 28, 29], "analysi": [0, 5, 6, 11, 20, 22, 24, 27, 28, 29], "analyt": [0, 16, 18], "ani": [13, 29], "anoth": [9, 29], "appli": 20, "approach": [0, 8, 14, 27, 30], "approxim": 12, "architectur": 1, "arrai": [21, 27], "assist": 25, "autocorrel": 24, "autograd": [2, 13, 30], "automat": [13, 30], "averag": 30, "b": 22, "back": [1, 11, 12, 28, 29], "background": [20, 22], "bag": 10, "base": [13, 30], "basic": [0, 5, 7, 9, 10, 11, 21, 28, 29], "batch": [1, 30], "bay": 5, "befor": 11, "better": 8, "bia": [6, 19, 22, 30], "binari": 1, "bind": 27, "bird": 10, "boldsymbol": [18, 28], "boost": 10, "bootstrap": [6, 10], "boston": [], "breast": 1, "brief": 27, "bring": 12, "build": [1, 3, 9], "c": [22, 27], "calcul": [18, 28, 29], "can": [27, 30], "cancer": [1, 7, 9, 11], "cart": 9, "case": [8, 10, 24, 28, 29], "central": [13, 20, 24, 29], "chain": 12, "challeng": 30, "chang": 10, "channel": 27, "chi": [0, 27], "choic": 17, "choos": [1, 30], "cifar01": 3, "classic": 11, "classif": [1, 9, 10], "classifi": 8, "clip": 1, "cluster": 14, "cnn": 3, "code": [1, 2, 5, 9, 11, 12, 13, 14, 15, 16, 22, 27, 28, 29, 30], "collect": [1, 3], "combin": 30, "commun": 27, "compar": [2, 10, 16], "comparison": 29, "compet": 30, "complet": 28, "complex": [0, 6, 22, 28], "complic": 6, "compon": 11, "comput": [9, 19, 30], "computerlab": 27, "con": [9, 30], "concept": 24, "condit": 29, "conjug": 13, "contn": 27, "converg": 30, "convex": [8, 13, 29], "convolut": [3, 12], "correct": 30, "correl": [11, 28], "correspond": [], "cost": [1, 10, 28, 29, 30], "cours": [20, 23, 26, 27], "covari": [5, 11, 24, 28], "cover": 27, "creat": 16, "cross": [6, 22], "cython": 27, "d": 22, "data": [0, 1, 3, 6, 7, 9, 11, 15, 17, 18, 20, 24, 27, 28], "dataset": [1, 3, 18], "david": 27, "deadlin": [22, 27], "deadllin": 25, "decai": [2, 30], "decis": [9, 10], "decomposit": [5, 11, 21, 28, 29], "deeep": [], "deep": [1, 2, 27], "defin": [1, 27], "degre": [0, 17, 28], "deliver": [15, 16], "deliveri": 22, "dens": 0, "deriv": [5, 12, 16, 17, 19, 28, 29, 30], "descent": [2, 10, 13, 18, 22, 29, 30], "design": 28, "detail": [3, 27], "develop": 1, "diagon": 11, "differ": [8, 30], "differenti": [2, 13, 30], "diffus": 2, "dimens": 30, "dimension": [2, 3, 8, 18], "disadvantag": 9, "discret": 24, "discrimin": 27, "distribut": [5, 24], "do": [1, 30], "doe": [28, 29], "domain": 24, "down": 1, "dropout": 1, "e": 22, "economi": [28, 29], "electron": 22, "element": [0, 24, 27], "elimin": 21, "energi": 27, "ensembl": 10, "entropi": 9, "environ": [0, 15], "equat": [0, 2, 12, 28, 29], "error": [0, 10, 27, 28, 29], "essenti": 27, "et": 30, "etc": 27, "euler": 2, "evalu": 1, "exampl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 27, 28, 29, 30], "exercis": [0, 6, 15, 16, 17, 18, 19, 28], "expect": [19, 24], "experi": 24, "explor": 0, "exponenti": [2, 30], "express": [16, 17, 19, 28], "extend": 29, "extrapol": 4, "extrem": [10, 27], "ey": 10, "f": 22, "fall": 25, "famili": [1, 27], "famou": 21, "fantast": [28, 29], "featur": [9, 16, 21, 28], "feed": [1, 12], "final": [12, 28, 30], "find": [16, 18], "fine": 1, "first": [4, 12, 27, 29], "fit": [0, 10, 15, 16, 27, 29], "fix": [28, 29, 30], "forc": 3, "forest": 10, "form": 18, "format": [22, 27], "formula": 18, "forward": [1, 2, 12], "foster": 27, "fourier": 3, "frank": 6, "freedom": [0, 17, 28], "frequent": [28, 30], "frequentist": [0, 27], "from": [5, 10, 12, 27, 28, 29, 30], "full": 2, "function": [0, 1, 6, 7, 8, 10, 11, 12, 13, 22, 24, 27, 28, 29, 30], "further": [3, 5, 28, 29], "g": 22, "gan": 4, "gaussian": 21, "gd": [13, 30], "gener": [4, 9, 27], "geometr": [11, 29], "gini": 9, "github": 15, "goal": [15, 16, 17, 18, 19], "good": [0, 27], "goodfellow": 30, "grade": [25, 27], "gradient": [1, 2, 10, 13, 18, 22, 29, 30], "growth": 2, "h": 22, "ha": 20, "handl": [21, 27], "hessian": [28, 29, 30], "hidden": 2, "hous": [], "how": 16, "hyperparamet": [1, 17], "hyperplan": 8, "i": [0, 1, 27], "id3": 9, "idea": 11, "ideal": 29, "ii": 27, "illustr": 29, "implement": [1, 16, 17, 18], "implic": [5, 28, 29], "import": [5, 21, 27, 28, 29], "improv": [1, 30], "includ": [13, 22, 30], "increment": 11, "index": 9, "inform": 25, "input": 2, "instal": [20, 22, 27], "instructor": 25, "interpret": [5, 11, 27, 28, 29], "introduc": [11, 13, 28], "introduct": [0, 6, 20, 21, 22, 27], "invers": [5, 21], "invert": [28, 29], "iter": 10, "its": 28, "jacobian": 28, "jax": 13, "julia": 27, "jungl": 10, "kera": [1, 3], "kernel": [8, 11], "lab": [29, 30], "lagrangian": 8, "lasso": [5, 6, 22, 28, 29], "last": [28, 30], "later": [5, 28, 29], "layer": [1, 2, 3, 12], "learn": [0, 1, 2, 11, 13, 14, 15, 16, 17, 18, 19, 20, 22, 27, 28, 29, 30], "least": [5, 6, 16, 19, 22, 27, 28, 29, 30], "lectur": [27, 29, 30], "level": 10, "librari": [20, 27], "likelihood": 7, "limit": [1, 13, 24, 29, 30], "linear": [0, 8, 13, 15, 21, 27, 28, 29], "link": [5, 11, 26, 28], "literatur": 22, "logist": [7, 27], "loss": [28, 29, 30], "lu": 21, "machin": [0, 8, 13, 20, 22, 27, 29], "main": [24, 27], "make": [0, 9, 10, 28], "mani": [10, 12], "mass": 27, "materi": [22, 27, 28, 29, 30], "math": [5, 28, 29], "mathemat": [3, 5, 8, 28, 29], "matric": [5, 21, 27], "matrix": [1, 5, 11, 12, 16, 21, 27, 28, 29, 30], "matter": 0, "max": 28, "mean": [0, 28, 29], "meet": [5, 10, 24, 27, 28], "mercer": 8, "method": [6, 9, 10, 13, 22, 27, 29, 30], "midnight": 22, "min": 28, "mini": 30, "minibatch": 30, "minim": 27, "ml": 27, "mlp": 12, "mnist": [3, 4], "model": [0, 1, 4, 6, 12, 15, 17, 27], "moment": 30, "momentum": [13, 22, 30], "mondai": [29, 30], "moon": [8, 9], "more": [3, 6, 21, 22, 27, 28, 29, 30], "motiv": 30, "move": 30, "multilay": 12, "multipl": [1, 3, 17], "multipli": 8, "need": [22, 27], "network": [1, 2, 3, 4, 7, 12, 27], "neural": [1, 2, 3, 4, 7, 12, 27], "new": [4, 18], "newton": [29, 30], "non": 8, "none": 30, "normal": [0, 1], "notat": 12, "note": [22, 28, 29], "now": [1, 9, 13, 29, 30], "nuclear": [0, 27], "numba": 27, "number": [0, 2, 24, 28, 30], "numer": [2, 22, 24], "numpi": [21, 27], "object": 3, "obtain": 11, "octob": 22, "od": 2, "off": [6, 19, 22], "ol": [5, 6, 15, 16, 18, 22, 29], "one": [2, 12, 18, 29], "oper": 21, "optim": [1, 8, 13, 18, 20, 27, 28, 29, 30], "order": [13, 18, 30], "ordinari": [5, 6, 16, 19, 22, 27, 28, 29, 30], "organ": [0, 27], "oslo": 26, "other": [4, 9, 11, 12, 21, 22, 27], "our": [0, 4, 5, 11, 13, 22, 27, 28, 29], "outcom": [20, 27], "output": 2, "overarch": [0, 4, 8, 9, 27, 28], "overview": [10, 27, 30], "own": [0, 10, 11, 22, 27, 28], "packag": [21, 27], "panda": [27, 28], "paramet": [27, 28], "paramt": 18, "part": [13, 20, 22, 29], "partial": 2, "pass": 1, "pca": 11, "pdf": 24, "perceptron": 12, "perform": [1, 9], "period": 3, "perspect": 1, "plan": [28, 29, 30], "plethora": 27, "point": 4, "poisson": 2, "polynomi": [3, 16, 18, 29], "popul": 2, "popular": 27, "practic": [13, 25, 27, 30], "pre": [1, 3], "preambl": 22, "predict": 4, "preprocess": [28, 30], "prerequisit": [3, 20, 27], "princip": 11, "principl": 3, "pro": [9, 30], "probabl": [5, 24], "problem": [1, 2, 13, 27, 28, 29, 30], "procedur": [9, 27], "process": [1, 3], "program": [2, 13, 22, 29, 30], "project": [6, 22, 25, 27], "prop": 13, "propag": [1, 12], "properti": [5, 24, 28, 29, 30], "python": [0, 9, 15, 20, 21, 27], "quick": 8, "r": 27, "random": [10, 11, 24], "raphson": 29, "rate": [22, 30], "read": [9, 27, 28, 30], "real": [6, 27], "recommend": [27, 28], "recurr": [4, 12], "reduc": [0, 28], "reduct": 3, "refer": 22, "reformul": 2, "regress": [0, 5, 6, 7, 9, 10, 13, 15, 17, 18, 19, 22, 27, 28, 29, 30], "regular": 1, "relat": [], "relev": [26, 28], "relu": 1, "remark": 3, "remind": [6, 8, 27, 28, 29, 30], "replac": [13, 30], "report": 22, "repositori": 15, "requir": [2, 20], "resampl": [6, 19, 22], "rescal": [6, 28], "residu": [28, 29], "resourc": 2, "result": [28, 29], "revisit": [13, 29, 30], "rewrit": [27, 28], "ridg": [0, 5, 6, 17, 18, 19, 22, 28, 29, 30], "rm": 13, "rmsprop": 30, "rule": [12, 30], "rung": 22, "same": [13, 30], "sampl": 11, "scale": [17, 18, 28, 30], "schedul": 27, "schemat": 9, "scheme": 2, "scienc": 27, "scikit": [0, 1, 11, 27, 28, 29, 30], "second": [13, 18, 30], "semest": 25, "sensit": 29, "septemb": [19, 29, 30], "session": [29, 30], "set": [0, 2, 3, 9, 12, 15, 23, 27, 28, 29], "setup": 15, "sgd": [13, 30], "should": 1, "similar": [13, 30], "simpl": [0, 4, 9, 13, 18, 27, 28, 29, 30], "simplest": 18, "singl": 10, "singular": [5, 11, 28, 29], "size": [28, 29, 30], "sklearn": 16, "slightli": 30, "sneak": 30, "soft": 8, "softmax": 1, "softwar": [22, 27], "solv": [2, 29], "solver": 13, "some": [13, 21, 28, 29], "specifi": 2, "split": [0, 15, 28], "squar": [0, 5, 6, 10, 16, 19, 22, 27, 28, 29, 30], "standard": [13, 28], "state": 0, "statist": [5, 6, 20, 24, 27], "steepest": [10, 13, 29], "step": 30, "stochast": [13, 22, 24, 30], "stop": 30, "strongli": 27, "suggest": 27, "summari": [25, 27], "superposit": 3, "supervis": 1, "support": 8, "svd": [5, 28, 29], "synthet": 18, "systemat": 3, "t": 28, "take": 16, "taken": [27, 30], "teach": 25, "teacher": [25, 27], "technic": 28, "techniqu": [6, 11, 22], "technologi": 20, "tensorflow": [1, 3], "tent": [25, 27], "test": [0, 1, 15, 17, 28], "text": 27, "textbook": [26, 27], "than": 29, "theorem": [5, 8, 11, 12, 24], "theori": 24, "theta": 18, "thi": 27, "time": 30, "tip": [13, 30], "togeth": 12, "tool": [22, 27], "top": 1, "topic": 27, "toward": 11, "trade": [6, 19, 22], "tradeoff": 6, "train": [0, 1, 4, 15, 27, 28], "transform": 3, "tree": [9, 10], "tuesdai": 29, "tune": 1, "two": [3, 8, 20], "type": [2, 4, 12, 27], "uio": 27, "univers": [12, 26], "unsupervis": 14, "up": [0, 2, 9, 12, 15, 27, 28, 29], "updat": [22, 30], "us": [0, 1, 2, 3, 7, 13, 16, 18, 20, 22, 27, 28, 29, 30], "v": [3, 30], "valid": [6, 22], "valu": [5, 11, 19, 24, 28, 29], "vari": 30, "variabl": [24, 29], "varianc": [6, 19, 22], "variou": 0, "vector": [8, 12, 16, 21, 27, 28], "versu": 27, "video": 30, "view": [0, 4, 10, 28], "virtual": 15, "visual": [1, 9], "wai": [9, 22], "wave": 2, "we": [27, 30], "wednesdai": 29, "week": [15, 16, 17, 18, 19, 27, 28, 29, 30], "weekli": [], "what": [0, 27, 28, 29], "when": 30, "which": [1, 30], "why": [27, 30], "wisconsin": 7, "write": [4, 11, 22, 29], "x": 28, "xgboost": 10, "yet": 29, "your": [0, 10, 16, 18, 22, 28]}}) \ No newline at end of file diff --git a/doc/LectureNotes/_build/html/statistics.html b/doc/LectureNotes/_build/html/statistics.html index 180953693..cd2f12154 100644 --- a/doc/LectureNotes/_build/html/statistics.html +++ b/doc/LectureNotes/_build/html/statistics.html @@ -231,7 +231,7 @@
    • Week 36: Linear Regression and Gradient descent
    • Exercises week 37
    • Week 37: Gradient descent methods
      • -
    • Exercises week 37
      • +
    • Exercises week 38

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

      @@ -2508,7 +2508,7 @@ centered matrix and/or vector that enter the fitting procedure.

      title="next page">

      next

      -

      Exercises week 37

      +

      Exercises week 38

      diff --git a/doc/LectureNotes/_build/jupyter_execute/exercisesweek38.ipynb b/doc/LectureNotes/_build/jupyter_execute/exercisesweek38.ipynb index a8c3a0e50..f0547694a 100644 --- a/doc/LectureNotes/_build/jupyter_execute/exercisesweek38.ipynb +++ b/doc/LectureNotes/_build/jupyter_execute/exercisesweek38.ipynb @@ -5,7 +5,7 @@ "id": "1da77599", "metadata": {}, "source": [ - "# Exercises week 37\n", + "# Exercises week 38\n", "## September 15-19\n", "\n", "## Resampling and the Bias-Variance Trade-off"