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Morten Hjorth-Jensen
2024-09-02 16:32:42 +02:00
parent 41f98033a3
commit 7fb0038ca1
7 changed files with 1220 additions and 925 deletions
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doc/pub/week36/html/._week36-bs001.html
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<li> Technicalities related to scaling and other issues with data handling</li>
<li> Linear Regression, ordinary least squares, Ridge and Lasso and links with Statistics</li>
<li> Recommended Reading: Goodfellow et al chapter 3 (till 3.11) on probability theory, see <a href="https://www.deeplearningbook.org/" target="_self"><tt>https://www.deeplearningbook.org/</tt></a></li>
<li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.
<!-- * <a href="https://youtu.be/Kc20CFK0z7Y" target="_self">Video of lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep7.pdf" target="_self">Whiteboard notes</a> --></li>
<li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.</li>
<li> <a href="https://youtu.be/oHjqjUB36KE" target="_self">Video of lecture</a></li>
<li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember2.pdf" target="_self">Whiteboard notes</a></li>
</ul>
<li> Material for the active learning sessions on Tuesday and Wednesday</li>
<ul>
doc/pub/week36/html/week36-reveal.html
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<p><li> Recommended Reading: Goodfellow et al chapter 3 (till 3.11) on probability theory, see <a href="https://www.deeplearningbook.org/" target="_blank"><tt>https://www.deeplearningbook.org/</tt></a></li>
<p><li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.
<!-- * <a href="https://youtu.be/Kc20CFK0z7Y" target="_blank">Video of lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep7.pdf" target="_blank">Whiteboard notes</a> --></li>
<p><li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.</li>
<p><li> <a href="https://youtu.be/oHjqjUB36KE" target="_blank">Video of lecture</a></li>
<p><li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember2.pdf" target="_blank">Whiteboard notes</a></li>
</ul>
<p>
<p><li> Material for the active learning sessions on Tuesday and Wednesday</li>
doc/pub/week36/html/week36-solarized.html
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@@ -246,9 +246,9 @@ MathJax.Hub.Config({
<li> Technicalities related to scaling and other issues with data handling</li>
<li> Linear Regression, ordinary least squares, Ridge and Lasso and links with Statistics</li>
<li> Recommended Reading: Goodfellow et al chapter 3 (till 3.11) on probability theory, see <a href="https://www.deeplearningbook.org/" target="_blank"><tt>https://www.deeplearningbook.org/</tt></a></li>
<li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.
<!-- * <a href="https://youtu.be/Kc20CFK0z7Y" target="_blank">Video of lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep7.pdf" target="_blank">Whiteboard notes</a> --></li>
<li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.</li>
<li> <a href="https://youtu.be/oHjqjUB36KE" target="_blank">Video of lecture</a></li>
<li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember2.pdf" target="_blank">Whiteboard notes</a></li>
</ul>
<li> Material for the active learning sessions on Tuesday and Wednesday</li>
<ul>
doc/pub/week36/html/week36.html
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@@ -323,9 +323,9 @@ MathJax.Hub.Config({
<li> Technicalities related to scaling and other issues with data handling</li>
<li> Linear Regression, ordinary least squares, Ridge and Lasso and links with Statistics</li>
<li> Recommended Reading: Goodfellow et al chapter 3 (till 3.11) on probability theory, see <a href="https://www.deeplearningbook.org/" target="_blank"><tt>https://www.deeplearningbook.org/</tt></a></li>
<li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.
<!-- * <a href="https://youtu.be/Kc20CFK0z7Y" target="_blank">Video of lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep7.pdf" target="_blank">Whiteboard notes</a> --></li>
<li> Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.</li>
<li> <a href="https://youtu.be/oHjqjUB36KE" target="_blank">Video of lecture</a></li>
<li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember2.pdf" target="_blank">Whiteboard notes</a></li>
</ul>
<li> Material for the active learning sessions on Tuesday and Wednesday</li>
<ul>
doc/pub/week36/ipynb/ipynb-week36-src.tar.gz
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doc/pub/week36/ipynb/week36.ipynb
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doc/src/week36/week36.do.txt
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@@ -11,8 +11,8 @@ DATE: September 2-6, 2024
* Linear Regression, ordinary least squares, Ridge and Lasso and links with Statistics
* Recommended Reading: Goodfellow et al chapter 3 (till 3.11) on probability theory, see URL:"https://www.deeplearningbook.org/"
* Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6 contain many useful hints which will also be relevant for the various projects as well.
# * "Video of lecture":"https://youtu.be/Kc20CFK0z7Y"
# * "Whiteboard notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesSep7.pdf"
* "Video of lecture":"https://youtu.be/oHjqjUB36KE"
* "Whiteboard notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember2.pdf"
* Material for the active learning sessions on Tuesday and Wednesday
* Summary from last week on discussion of SVD, Ridge and Lasso linear regression.
* Raschka et al, chapter 4 pages 105-134 and chapter 6 pages 171-185. Chapter 4 and 6, as for the lecture discussion