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Morten Hjorth-Jensen
2024-10-08 17:04:26 +02:00
parent 87d1e4455c
commit dbbebedb06
114 changed files with 3736 additions and 1751 deletions
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@@ -308,6 +308,21 @@ const thebe_selector_output = ".output, .cell_output"
Week 39: Optimization and Gradient Methods
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="week40.html">
Week 40: Gradient descent methods (continued) and start Neural networks
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="exercisesweek41.html">
Exercises week 41
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<li class="toctree-l1">
<a class="reference internal" href="week41.html">
Week 41 Neural networks and constructing a neural network code
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</li>
</ul>
<p aria-level="2" class="caption" role="heading">
<span class="caption-text">
@@ -320,6 +335,11 @@ const thebe_selector_output = ".output, .cell_output"
Project 1 on Machine Learning, deadline October 7 (midnight), 2024
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</li>
<li class="toctree-l1">
<a class="reference internal" href="project2.html">
Project 2 on Machine Learning, deadline November 4 (Midnight)
</a>
</li>
</ul>
</div>
@@ -1285,10 +1305,10 @@ covariance matrix through the <strong>np.linalg.eig()</strong> function.</p>
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>-0.024792624800382218
3.9225384545636204
[[0.94623184 2.84401886]
[2.84401886 9.4477214 ]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>-0.009134699065945493
4.0244965108017645
[[0.85613835 2.50655379]
[2.50655379 8.3404509 ]]
</pre></div>
</div>
</div>
@@ -1325,10 +1345,10 @@ a more brute force way. Here we scale the mean values for each column of the des
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.08536248571780691
1.8207274870895702
[[1. 0.74900488]
[0.74900488 1. ]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.07971187802560528
1.800782161095708
[[1. 0.59411814]
[0.59411814 1. ]]
</pre></div>
</div>
</div>
@@ -1358,32 +1378,30 @@ this matrix we easily see that it is a positive definite matrix.</p>
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[ 1.10115017 1.66431407]
[ 0.12043521 1.32305911]
[-1.30023144 -3.36154104]
[-0.25200841 -1.11277166]
[-1.55102329 -4.20158083]
[ 0.72770687 0.97206657]
[ 0.76533281 2.10747579]
[-0.20666447 0.79623487]
[-0.63919355 -2.48490503]
[ 1.23449607 4.29764815]]
</pre></div>
</div>
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span> 0 1
0 1.101150 1.664314
1 0.120435 1.323059
2 -1.300231 -3.361541
3 -0.252008 -1.112772
4 -1.551023 -4.201581
5 0.727707 0.972067
6 0.765333 2.107476
7 -0.206664 0.796235
8 -0.639194 -2.484905
9 1.234496 4.297648
0 1
0 1.0000 0.9434
1 0.9434 1.0000
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[ 0.81395716 1.89155934]
[-1.34726166 -4.13453411]
[-0.46229544 -2.34061974]
[ 0.24429334 1.4051634 ]
[ 0.41971814 1.6405671 ]
[ 2.02456235 5.03973227]
[-1.97311824 -4.72521196]
[ 0.10738656 0.24578123]
[-0.52702419 -2.34023682]
[ 0.69978197 3.31779928]]
0 1
0 0.813957 1.891559
1 -1.347262 -4.134534
2 -0.462295 -2.340620
3 0.244293 1.405163
4 0.419718 1.640567
5 2.024562 5.039732
6 -1.973118 -4.725212
7 0.107387 0.245781
8 -0.527024 -2.340237
9 0.699782 3.317799
0 1
0 1.000000 0.969413
1 0.969413 1.000000
</pre></div>
</div>
</div>
@@ -1440,37 +1458,37 @@ this matrix we easily see that it is a positive definite matrix.</p>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span> 0 1 2 3 4 5 6 7 \
0 0.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
1 0.0 0.083179 0.086483 0.081217 0.083548 0.086239 0.072037 0.073514
2 0.0 0.086483 0.091362 0.082533 0.085853 0.089626 0.071638 0.073800
3 0.0 0.081217 0.082533 0.084963 0.086068 0.087429 0.079030 0.079670
4 0.0 0.083548 0.085853 0.086068 0.087871 0.089996 0.078945 0.080094
5 0.0 0.086239 0.089626 0.087429 0.089996 0.092956 0.079002 0.080706
6 0.0 0.072037 0.071638 0.079030 0.078945 0.079002 0.076071 0.075876
7 0.0 0.073514 0.073800 0.079670 0.080094 0.080706 0.075876 0.076066
8 0.0 0.075289 0.076321 0.080549 0.081527 0.082742 0.075842 0.076448
9 0.0 0.077391 0.079240 0.081686 0.083268 0.085145 0.075978 0.077035
10 0.0 0.063786 0.062216 0.072380 0.071437 0.070552 0.071436 0.070622
11 0.0 0.064606 0.063536 0.072591 0.072031 0.071560 0.071049 0.070531
12 0.0 0.065654 0.065121 0.072997 0.072849 0.072826 0.070805 0.070605
13 0.0 0.066948 0.067000 0.073612 0.073911 0.074374 0.070712 0.070855
14 0.0 0.068512 0.069203 0.074454 0.075239 0.076232 0.070780 0.071294
1 0.0 0.092746 0.090302 0.090561 0.088058 0.085463 0.081530 0.078898
2 0.0 0.090302 0.088694 0.089052 0.086797 0.084423 0.080286 0.077782
3 0.0 0.090561 0.089052 0.095106 0.092533 0.089858 0.089404 0.086489
4 0.0 0.088058 0.086797 0.092533 0.090114 0.087585 0.086913 0.084127
5 0.0 0.085463 0.084423 0.089858 0.087585 0.085197 0.084340 0.081681
6 0.0 0.081530 0.080286 0.089404 0.086913 0.084340 0.086471 0.083596
7 0.0 0.078898 0.077782 0.086489 0.084127 0.081681 0.083596 0.080849
8 0.0 0.076334 0.075334 0.083645 0.081405 0.079080 0.080793 0.078170
9 0.0 0.073841 0.072946 0.080875 0.078753 0.076543 0.078067 0.075562
10 0.0 0.072973 0.071789 0.082361 0.079982 0.077541 0.081296 0.078544
11 0.0 0.070485 0.069391 0.079518 0.077254 0.074928 0.078454 0.075823
12 0.0 0.068088 0.067077 0.076777 0.074622 0.072404 0.075712 0.073198
13 0.0 0.065778 0.064845 0.074134 0.072083 0.069970 0.073071 0.070667
14 0.0 0.063554 0.062693 0.071588 0.069637 0.067623 0.070527 0.068229
8 9 10 11 12 13 14
0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
1 0.075289 0.077391 0.063786 0.064606 0.065654 0.066948 0.068512
2 0.076321 0.079240 0.062216 0.063536 0.065121 0.067000 0.069203
3 0.080549 0.081686 0.072380 0.072591 0.072997 0.073612 0.074454
4 0.081527 0.083268 0.071437 0.072031 0.072849 0.073911 0.075239
5 0.082742 0.085145 0.070552 0.071560 0.072826 0.074374 0.076232
6 0.075842 0.075978 0.071436 0.071049 0.070805 0.070712 0.070780
7 0.076448 0.077035 0.070622 0.070531 0.070605 0.070855 0.071294
8 0.077280 0.078359 0.069907 0.070135 0.070552 0.071173 0.072015
9 0.078359 0.079976 0.069293 0.069866 0.070655 0.071680 0.072961
10 0.069907 0.069293 0.068353 0.067515 0.066778 0.066145 0.065619
11 0.070135 0.069866 0.067515 0.066912 0.066425 0.066059 0.065821
12 0.070552 0.070655 0.066778 0.066425 0.066205 0.066127 0.066199
13 0.071173 0.071680 0.066145 0.066059 0.066127 0.066358 0.066766
14 0.072015 0.072961 0.065619 0.065821 0.066199 0.066766 0.067539
1 0.076334 0.073841 0.072973 0.070485 0.068088 0.065778 0.063554
2 0.075334 0.072946 0.071789 0.069391 0.067077 0.064845 0.062693
3 0.083645 0.080875 0.082361 0.079518 0.076777 0.074134 0.071588
4 0.081405 0.078753 0.079982 0.077254 0.074622 0.072083 0.069637
5 0.079080 0.076543 0.077541 0.074928 0.072404 0.069970 0.067623
6 0.080793 0.078067 0.081296 0.078454 0.075712 0.073071 0.070527
7 0.078170 0.075562 0.078544 0.075823 0.073198 0.070667 0.068229
8 0.075609 0.073115 0.075864 0.073260 0.070747 0.068324 0.065989
9 0.073115 0.070730 0.073260 0.070769 0.068364 0.066044 0.063809
10 0.075864 0.073260 0.077608 0.074866 0.072223 0.069676 0.067224
11 0.073260 0.070769 0.074866 0.072241 0.069711 0.067273 0.064924
12 0.070747 0.068364 0.072223 0.069711 0.067288 0.064954 0.062705
13 0.068324 0.066044 0.069676 0.067273 0.064954 0.062719 0.060565
14 0.065989 0.063809 0.067224 0.064924 0.062705 0.060565 0.058503
</pre></div>
</div>
</div>