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@@ -55,7 +55,8 @@ const thebe_selector_output = ".output, .cell_output"
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@@ -312,6 +313,26 @@ const thebe_selector_output = ".output, .cell_output"
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Week 40: Gradient descent methods (continued) and start Neural networks
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Exercises week 41
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Week 41 Neural networks and constructing a neural network code
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Exercises week 42
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<a class="reference internal" href="week42.html">
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Week 42 Constructing a Neural Network code with introduction to Tensor flow
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@@ -324,6 +345,11 @@ const thebe_selector_output = ".output, .cell_output"
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Project 1 on Machine Learning, deadline October 9 (midnight), 2023
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<a class="reference internal" href="project2.html">
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Project 2 on Machine Learning, deadline November 13 (Midnight)
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@@ -674,7 +700,7 @@ which polynomial fits the data best.</p>
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<div class="cell_output docutils container">
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_19329/39730396.py:11: MatplotlibDeprecationWarning: Calling gca() with keyword arguments was deprecated in Matplotlib 3.4. Starting two minor releases later, gca() will take no keyword arguments. The gca() function should only be used to get the current axes, or if no axes exist, create new axes with default keyword arguments. To create a new axes with non-default arguments, use plt.axes() or plt.subplot().
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/var/folders/td/3yk470mj5p931p9dtkk0y6jw0000gn/T/ipykernel_31707/39730396.py:11: MatplotlibDeprecationWarning: Calling gca() with keyword arguments was deprecated in Matplotlib 3.4. Starting two minor releases later, gca() will take no keyword arguments. The gca() function should only be used to get the current axes, or if no axes exist, create new axes with default keyword arguments. To create a new axes with non-default arguments, use plt.axes() or plt.subplot().
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ax = fig.gca(projection='3d')
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</pre></div>
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@@ -1033,13 +1059,20 @@ of code developers and contributors keeps increasing.</p>
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<p class="prev-next-title">Week 42 Constructing a Neural Network code with introduction to Tensor flow</p>
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