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update week 39

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Morten Hjorth-Jensen
2024-09-23 12:48:19 +02:00
parent 18cbaf20ff
commit 5e7f6370d2
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doc/pub/week38/ipynb/w38KHBiasVariance.ipynb
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doc/pub/week38/ipynb/week38.ipynb
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@@ -208,9 +208,11 @@ MathJax.Hub.Config({
<p><li> Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of gradient methods</li>
<p><li> Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).
<!-- * <a href="https://youtu.be/bFRVuIJroHs" target="_blank">Video of lecture</a> -->
<!-- * Whiteboard notes TBA at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep28.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep28.pdf</tt></a> --></li>
<p><li> Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).</li>
<p><li> <a href="https://youtu.be/ISGpTC28Vmk" target="_blank">Video of lecture</a></li>
<p><li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember23.pdf" target="_blank">Whiteboard notes</a></li>
<p><li> Readings and Videos:</li>
<ul>
doc/pub/week39/html/week39-solarized.html
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<p>
<ul>
<li> Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of gradient methods</li>
<li> Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).
<!-- * <a href="https://youtu.be/bFRVuIJroHs" target="_blank">Video of lecture</a> -->
<!-- * Whiteboard notes TBA at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep28.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep28.pdf</tt></a> --></li>
<li> Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).</li>
<li> <a href="https://youtu.be/ISGpTC28Vmk" target="_blank">Video of lecture</a></li>
<li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember23.pdf" target="_blank">Whiteboard notes</a></li>
<li> Readings and Videos:</li>
<ul>
<li> These lecture notes</li>
doc/pub/week39/html/week39.html
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<p>
<ul>
<li> Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of gradient methods</li>
<li> Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).
<!-- * <a href="https://youtu.be/bFRVuIJroHs" target="_blank">Video of lecture</a> -->
<!-- * Whiteboard notes TBA at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep28.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep28.pdf</tt></a> --></li>
<li> Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).</li>
<li> <a href="https://youtu.be/ISGpTC28Vmk" target="_blank">Video of lecture</a></li>
<li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember23.pdf" target="_blank">Whiteboard notes</a></li>
<li> Readings and Videos:</li>
<ul>
<li> These lecture notes</li>
doc/pub/week39/ipynb/ipynb-week39-src.tar.gz
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doc/pub/week39/ipynb/week39.ipynb
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doc/src/week39/week39.do.txt
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@@ -13,8 +13,8 @@ DATE: Week 39
!bblock Material for the lecture on Monday September 23
* Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of gradient methods
* Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).
# * "Video of lecture":"https://youtu.be/bFRVuIJroHs"
# * Whiteboard notes TBA at URL:"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep28.pdf"
* "Video of lecture":"https://youtu.be/ISGpTC28Vmk"
* "Whiteboard notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember23.pdf"
* Readings and Videos:
* These lecture notes
* For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.