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doc/LectureNotes/_build/html/chapter1.html

@@ -343,6 +343,16 @@ const thebe_selector_output = ".output, .cell_output"
    Week 43: Deep Learning: Constructing a Neural Network code and solving differential equations
   </a>
  </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="week44.html">
+   Week 44,  Convolutional Neural Networks (CNN)
+  </a>
+ </li>
+ <li class="toctree-l1">
+  <a class="reference internal" href="week45.html">
+   Week 45,  Recurrent Neural Networks
+  </a>
+ </li>
 </ul>
 <p aria-level="2" class="caption" role="heading">
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@@ -1076,13 +1086,13 @@ example of the functionality of <strong>Scikit-Learn</strong>.</p>
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 <div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>The intercept alpha: 
- [1.95815651]
+ [1.79503422]
 Coefficient beta : 
- [[5.03219974]]
-Mean squared error: 0.26
-Variance score: 0.90
+ [[5.33918941]]
+Mean squared error: 0.21
+Variance score: 0.92
 Mean squared log error: 0.01
-Mean absolute error: 0.41
+Mean absolute error: 0.37
 </pre></div>
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 <img alt="_images/chapter1_19_1.png" src="_images/chapter1_19_1.png" />
@@ -1182,7 +1192,7 @@ a linear <span class="math notranslate nohighlight">\(x\)</span>-dependence we s
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 <img alt="_images/chapter1_33_0.png" src="_images/chapter1_33_0.png" />
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.004999999999999996
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.005
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