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Morten Hjorth-Jensen
2023-11-21 06:16:54 +01:00
parent a854a3e9c0
commit 06b09eb681
173 changed files with 13894 additions and 3718 deletions
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doc/LectureNotes/_build/html/linalg.html
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@@ -353,6 +353,16 @@ const thebe_selector_output = ".output, .cell_output"
Week 45, Recurrent Neural Networks
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="week46.html">
Week 46: Decision Trees, Ensemble methods and Random Forests
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="week47.html">
Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods and Summary of Course
</a>
</li>
</ul>
<p aria-level="2" class="caption" role="heading">
<span class="caption-text">
@@ -367,7 +377,12 @@ const thebe_selector_output = ".output, .cell_output"
</li>
<li class="toctree-l1">
<a class="reference internal" href="project2.html">
Project 2 on Machine Learning, deadline November 13 (Midnight)
Project 2 on Machine Learning, deadline November 17 (Midnight)
</a>
</li>
<li class="toctree-l1">
<a class="reference internal" href="project3.html">
Project 3 on Machine Learning, deadline December 18 (midnight), 2023
</a>
</li>
</ul>
@@ -673,8 +688,8 @@ matrices and vectors.</p>
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[ 0.44079937 -0.14839786 -1.00862798 -0.22996417 0.53459992 0.28570701
-0.40043644 0.43989497 -0.27463692 -0.17644873]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[-0.35325013 1.40714201 -1.34943652 0.57794243 -0.3501046 -0.08502551
0.22939767 0.37351692 0.87604059 -0.16082975]
</pre></div>
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@@ -895,26 +910,26 @@ 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>[[0.51727541 0.09312344 0.68284332 0.10399743 0.11110246 0.17604689
0.83716603 0.72598009 0.89142728 0.54640368]
[0.33656494 0.55847112 0.87450434 0.13621148 0.38488879 0.68655761
0.74147751 0.2544422 0.33708747 0.6848187 ]
[0.54213329 0.22197349 0.8702764 0.36674564 0.59816099 0.3225819
0.18856622 0.88595314 0.46132345 0.55685628]
[0.88866133 0.65822169 0.05062537 0.20513942 0.41671085 0.48333258
0.12786653 0.31532451 0.56548318 0.65766777]
[0.55206229 0.11704038 0.2856881 0.26961519 0.13371503 0.26805987
0.34460089 0.09215672 0.53367133 0.34362409]
[0.34642944 0.54617756 0.22752605 0.86192438 0.49901588 0.98157799
0.69802962 0.6513444 0.88050263 0.66725024]
[0.88657125 0.3591093 0.14600426 0.66667985 0.95921115 0.09607524
0.0470705 0.42777999 0.65318467 0.59602968]
[0.37187359 0.6945612 0.7840642 0.78347558 0.60307141 0.95682858
0.99534399 0.1859082 0.4281152 0.11232098]
[0.8459616 0.64874236 0.39148625 0.284499 0.35322418 0.37391132
0.39837199 0.47950427 0.44298022 0.31921368]
[0.89881513 0.0062825 0.19942021 0.86850693 0.90715001 0.3426926
0.98597638 0.71365128 0.79367372 0.86629645]]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[[0.79473273 0.85144525 0.58083888 0.95534385 0.74978227 0.09375511
0.3762603 0.55342366 0.69948916 0.52180757]
[0.41125816 0.53375204 0.78459969 0.63860117 0.68632877 0.3135197
0.64378812 0.1228485 0.23374497 0.16365729]
[0.06106228 0.41042542 0.72277345 0.87499269 0.25312591 0.97624609
0.30902533 0.35567049 0.01001307 0.60893494]
[0.68303739 0.09712817 0.45884458 0.56841764 0.80038919 0.6266335
0.15169011 0.58487995 0.78177874 0.84856859]
[0.35193678 0.09087594 0.88887574 0.11148997 0.77155539 0.02374036
0.0382287 0.46294168 0.72359843 0.78427913]
[0.97784379 0.14479759 0.46138883 0.85159661 0.18534538 0.96863656
0.84143964 0.01707943 0.61695829 0.41936371]
[0.00693764 0.08822806 0.64624281 0.59033885 0.00622235 0.56069111
0.11141718 0.8736902 0.22015945 0.70367282]
[0.55011282 0.56603693 0.98849276 0.79256181 0.97555188 0.731344
0.50153896 0.88292369 0.05203331 0.10856388]
[0.73582138 0.28478815 0.03418359 0.54608238 0.33959063 0.34619711
0.93037027 0.31960205 0.97702512 0.13990198]
[0.48668089 0.23908241 0.22812848 0.56640341 0.8840647 0.56933711
0.46660343 0.91471524 0.52960552 0.85067652]]
</pre></div>
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@@ -974,13 +989,13 @@ 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>-0.10095106250934528
3.73293228266057
-0.589971818845805
[[ 1.44967228 4.20536556 4.14179769]
[ 4.20536556 13.10814421 12.2161908 ]
[ 4.14179769 12.2161908 17.03056169]]
[28.710746 0.0846527 2.79297948]
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.13443663368799186
4.256841168348422
0.26403986587386163
[[0.69773572 2.0163462 1.40881429]
[2.0163462 6.97266041 4.00255459]
[1.40881429 4.00255459 5.66675932]]
[10.95984465 0.0898612 2.2874496 ]
</pre></div>
</div>
</div>