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Morten Hjorth-Jensen
2024-11-03 14:50:52 +01:00
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doc/LectureNotes/_build/html/linalg.html
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@@ -353,6 +353,11 @@ const thebe_selector_output = ".output, .cell_output"
Week 44, Convolutional Neural Networks (CNN)
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</li>
<li class="toctree-l1">
<a class="reference internal" href="week45.html">
Week 45, Convolutional Neural Networks (CCNs) and Recurrent Neural Networks (RNNs)
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</ul>
<p aria-level="2" class="caption" role="heading">
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@@ -673,8 +678,8 @@ matrices and vectors.</p>
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<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[ 0.32001824 -0.74192227 0.29589074 0.79474214 0.93002171 -0.3039884
-0.23453753 0.42163714 0.38469469 -0.16425426]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[-0.16520328 1.62291487 -1.6087843 0.42672668 -0.54245399 -0.47389944
1.54395649 0.30474374 0.88958816 1.67644921]
</pre></div>
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@@ -895,26 +900,26 @@ as (recall that we user lowercase letters for vectors and uppercase letters for
</div>
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<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[0.82195744 0.3891388 0.6393255 0.23848657 0.94055712 0.09024338
0.37413588 0.74761567 0.35435219 0.07518155]
[0.38479849 0.78036158 0.21824173 0.13664315 0.21480211 0.52460926
0.89595918 0.25702102 0.46918325 0.00800661]
[0.48745365 0.65375675 0.41048039 0.738242 0.68043741 0.42684131
0.68546404 0.40826579 0.52793214 0.7031337 ]
[0.07395645 0.49563003 0.53379115 0.81702472 0.00841458 0.72858608
0.30840554 0.47836061 0.2180387 0.45175115]
[0.36057178 0.55188499 0.48122761 0.1403625 0.56938055 0.04170341
0.81077908 0.74066856 0.87234539 0.77231525]
[0.4271294 0.25172651 0.83065295 0.37772591 0.79299228 0.80941284
0.51579138 0.45860296 0.80070169 0.07136868]
[0.00355788 0.63534832 0.84438755 0.30356855 0.20488577 0.24956991
0.06192181 0.42523073 0.09314326 0.14371995]
[0.74985547 0.10252946 0.3477494 0.32907268 0.41745457 0.38472307
0.16382994 0.55656086 0.84104054 0.03111555]
[0.83749554 0.84073416 0.69347409 0.82022408 0.04823618 0.34401751
0.72546035 0.60205311 0.22177506 0.58325333]
[0.30521597 0.84357837 0.8955058 0.17549914 0.96618572 0.86987923
0.03103759 0.44019341 0.30819287 0.07016861]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[0.28784593 0.96321926 0.20866637 0.95849867 0.92941344 0.1506968
0.22840543 0.0920889 0.80793317 0.50389563]
[0.17183189 0.20143625 0.45450913 0.00646788 0.86626878 0.08925572
0.52334702 0.03991659 0.35369204 0.78536632]
[0.16039093 0.84796642 0.82292496 0.94439363 0.30258327 0.61219766
0.73629812 0.16934353 0.17379702 0.04679308]
[0.63996185 0.11274165 0.25945116 0.89423541 0.22346992 0.21007634
0.36949491 0.48033198 0.62082039 0.32646485]
[0.74365467 0.7733283 0.7928694 0.77278596 0.58641617 0.32914379
0.84818156 0.91522307 0.69515573 0.58154488]
[0.31956141 0.10975592 0.3919079 0.90613668 0.5978168 0.96954883
0.92380565 0.41038312 0.32288529 0.55800813]
[0.81494889 0.50633361 0.99792993 0.31899022 0.78486135 0.8728734
0.01932215 0.67005078 0.19206115 0.83068485]
[0.83903596 0.48440335 0.66923495 0.46990302 0.80674666 0.96465867
0.23114262 0.71841354 0.23608218 0.10929587]
[0.94970686 0.08965584 0.07768608 0.19814125 0.38472539 0.36807444
0.29740527 0.95391872 0.21994185 0.13166051]
[0.88743493 0.10721234 0.91281804 0.15125714 0.58166986 0.37588174
0.12925014 0.00524148 0.93747994 0.33514166]]
</pre></div>
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@@ -974,13 +979,13 @@ covariance matrix through the <strong>np.linalg.eig()</strong> function.</p>
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<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>-0.0005546012958340718
4.201607904119753
-0.10755063024965804
[[ 1.0024984 3.08394521 3.01944109]
[ 3.08394521 10.46598005 8.68420144]
[ 3.01944109 8.68420144 13.58893352]]
[21.74071459 0.05707756 3.25961982]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>-0.08051403053372341
3.7140333805249566
-0.380671880038213
[[ 0.92926923 2.65811424 2.52618757]
[ 2.65811424 8.74246828 7.24691709]
[ 2.52618757 7.24691709 11.65085456]]
[18.34869216 0.09587752 2.87802239]
</pre></div>
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