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Morten Hjorth-Jensen
2024-10-21 13:45:48 +02:00
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commit de6a6d8bcb
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doc/LectureNotes/_build/html/linalg.html
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@@ -343,6 +343,11 @@ const thebe_selector_output = ".output, .cell_output"
Week 43: Deep Learning: Constructing a Neural Network code and solving differential equations
</a>
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<li class="toctree-l1">
<a class="reference internal" href="exercisesweek43.html">
Exercises week 43
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<p aria-level="2" class="caption" role="heading">
<span class="caption-text">
@@ -663,8 +668,8 @@ matrices and vectors.</p>
</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>[-0.16146139 -0.24200844 -0.43506123 -0.19800999 -0.44832989 -1.49768808
0.43836612 -1.45052717 -0.76587916 0.22929165]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[-0.08059005 0.26043697 0.54190252 -0.8321864 1.74960664 0.28855565
1.03029311 -0.54136139 0.94583038 0.99378218]
</pre></div>
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@@ -885,26 +890,26 @@ 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>[[0.93164299 0.26835242 0.93001752 0.24829629 0.34832197 0.77112374
0.42590512 0.36694417 0.51860019 0.03241936]
[0.051782 0.7721643 0.87478387 0.96734276 0.59958693 0.96084123
0.84869686 0.4488194 0.76561858 0.07510785]
[0.26590299 0.6561141 0.87736602 0.5088893 0.08090942 0.77313451
0.7024611 0.95132723 0.72184754 0.60480445]
[0.01562424 0.15670465 0.82204612 0.8859754 0.42439452 0.82934918
0.55678525 0.72754455 0.65765268 0.65295017]
[0.55148543 0.11596287 0.12675974 0.63520537 0.81012733 0.50505108
0.65976951 0.62246687 0.77878621 0.48944878]
[0.31068981 0.26956051 0.24188439 0.28098147 0.31739522 0.47130422
0.34488863 0.39503373 0.71143744 0.95882586]
[0.91507022 0.58570955 0.28341932 0.03647182 0.51045268 0.31216736
0.94607554 0.37468967 0.17285183 0.29134342]
[0.13728124 0.92004534 0.81825652 0.82133401 0.54874017 0.45538713
0.85189083 0.09919725 0.39730902 0.46053947]
[0.49503632 0.30593976 0.18180717 0.31186409 0.7337962 0.78380113
0.56237849 0.92761972 0.25034533 0.39919362]
[0.37705573 0.05706322 0.70277293 0.90232941 0.83915415 0.62571719
0.85724692 0.9308197 0.91496317 0.52038652]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[0.77235007 0.27529208 0.31199504 0.17293829 0.82162246 0.13378194
0.90679215 0.39664124 0.3121824 0.13861839]
[0.69473608 0.72612916 0.4570065 0.41275555 0.76067335 0.56239325
0.33900003 0.83105136 0.14230327 0.04713857]
[0.62377027 0.12392385 0.7500676 0.67969567 0.15971479 0.97072608
0.00183119 0.95291169 0.59353543 0.03550103]
[0.99152919 0.13537597 0.88366546 0.73118203 0.82120582 0.53939154
0.01958776 0.59647764 0.17941609 0.34647125]
[0.43263402 0.2754374 0.59137018 0.52019078 0.71121535 0.60648493
0.94665557 0.66298436 0.22615136 0.29639686]
[0.84424529 0.59603845 0.9219476 0.44909201 0.67715931 0.18908167
0.76516101 0.38007856 0.83478186 0.75271427]
[0.53862422 0.11323706 0.15316333 0.34540564 0.81994631 0.52292446
0.26760957 0.02430273 0.03576146 0.67801091]
[0.52928925 0.14990609 0.86292532 0.43014974 0.83844809 0.04560463
0.84163178 0.80868063 0.8371938 0.39611129]
[0.12607006 0.5113303 0.63901709 0.99976659 0.34756595 0.28622513
0.89290901 0.84314251 0.31916189 0.29920799]
[0.23476091 0.40074419 0.21933245 0.48906993 0.19899282 0.06752501
0.85079729 0.64275853 0.33164051 0.08304321]]
</pre></div>
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@@ -964,13 +969,13 @@ 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>-0.051916914594944144
4.063621005600529
-0.19857342950283463
[[ 0.98101481 3.10179509 3.46796873]
[ 3.10179509 10.80421021 10.86493273]
[ 3.46796873 10.86493273 18.60084189]]
[27.06474536 0.07037089 3.25095067]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>-0.04071979724729911
4.064820972167253
-0.3254718508870977
[[0.88727586 2.57584621 2.19767225]
[2.57584621 8.44132765 6.34964801]
[2.19767225 6.34964801 9.99322469]]
[16.34233281 0.08212093 2.89737445]
</pre></div>
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