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Morten Hjorth-Jensen
2023-10-05 16:32:17 +02:00
parent 4b847a0d95
commit ec511fb068
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doc/pub/week40/html/._week40-bs001.html
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@@ -339,7 +339,9 @@ MathJax.Hub.Config({
<!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
<ul>
<li> Stochastic Gradient descent with examples and automatic differentiation</li>
<li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
<li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
<li> <a href="https://youtu.be/75pr3hKY20U" target="_self">Video of lecture</a></li>
<li> "Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf</tt></a></li>
<li> Readings and Videos:</li>
<ul>
<li> These lecture notes</li>
doc/pub/week40/html/week40-reveal.html
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<p><li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
<p><li> <a href="https://youtu.be/75pr3hKY20U" target="_blank">Video of lecture</a></li>
<p><li> "Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf</tt></a></li>
<p><li> Readings and Videos:</li>
<ul>
doc/pub/week40/html/week40-solarized.html
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<p>
<ul>
<li> Stochastic Gradient descent with examples and automatic differentiation</li>
<li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
<li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
<li> <a href="https://youtu.be/75pr3hKY20U" target="_blank">Video of lecture</a></li>
<li> "Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf</tt></a></li>
<li> Readings and Videos:</li>
<ul>
<li> These lecture notes</li>
doc/pub/week40/html/week40.html
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@@ -372,7 +372,9 @@ MathJax.Hub.Config({
<p>
<ul>
<li> Stochastic Gradient descent with examples and automatic differentiation</li>
<li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
<li> Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.</li>
<li> <a href="https://youtu.be/75pr3hKY20U" target="_blank">Video of lecture</a></li>
<li> "Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf" target="_blank"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.pdf</tt></a></li>
<li> Readings and Videos:</li>
<ul>
<li> These lecture notes</li>
doc/pub/week40/ipynb/ipynb-week40-src.tar.gz
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doc/pub/week40/ipynb/week40.ipynb
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doc/src/week40/week40.do.txt
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@@ -18,7 +18,9 @@ DATE: October 2-6, 2023
!bblock Material for the lecture on Thursday October 5, 2023
* Stochastic Gradient descent with examples and automatic differentiation
* Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.
* Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model.
* "Video of lecture":"https://youtu.be/75pr3hKY20U"
* "Whiteboard notes at URL:"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesOct5.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.