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update. week 38

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Morten Hjorth-Jensen
2025-09-14 09:04:00 +02:00
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commit 8dd0f7db27
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doc/LectureNotes/week38.ipynb
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doc/pub/week37/ipynb/week37.ipynb
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doc/pub/week38/html/._week38-bs001.html
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@@ -259,7 +259,7 @@ MathJax.Hub.Config({
<ol>
<li> Statistical interpretation of Ridge and Lasso regression</li>
<li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff (this may partly be discussed during the exercise sessions as well.</li>
<li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/" target="_self"><tt>https://youtu.be/</tt></a>
<li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_self"><tt>https://youtu.be/J_41Hld6tTU</tt></a>
<!-- * <a href="https://youtu.be/omLmp_kkie0" target="_self">Video of Lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember9.pdf" target="_self">Whiteboard notes</a> --></li>
</ol>
doc/pub/week38/html/._week38-bs042.html
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@@ -260,6 +260,8 @@ the jupyter-notebook from week 37 (September 12-16).
</p>
<p>For the lab session, the following video on cross validation (from 2024), could be helpful, see <a href="https://www.youtube.com/watch?v=T9jjWsmsd1o" target="_self"><tt>https://www.youtube.com/watch?v=T9jjWsmsd1o</tt></a></p>
<p>See also video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_self"><tt>https://youtu.be/J_41Hld6tTU</tt></a></p>
<p>
<!-- navigation buttons at the bottom of the page -->
<ul class="pagination">
doc/pub/week38/html/week38-reveal.html
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@@ -200,7 +200,7 @@ MathJax.Hub.Config({
<ol>
<p><li> Statistical interpretation of Ridge and Lasso regression</li>
<p><li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff (this may partly be discussed during the exercise sessions as well.</li>
<p><li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/" target="_blank"><tt>https://youtu.be/</tt></a>
<p><li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a>
<!-- * <a href="https://youtu.be/omLmp_kkie0" target="_blank">Video of Lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember9.pdf" target="_blank">Whiteboard notes</a> --></li>
</ol>
@@ -1830,6 +1830,8 @@ the jupyter-notebook from week 37 (September 12-16).
</p>
<p>For the lab session, the following video on cross validation (from 2024), could be helpful, see <a href="https://www.youtube.com/watch?v=T9jjWsmsd1o" target="_blank"><tt>https://www.youtube.com/watch?v=T9jjWsmsd1o</tt></a></p>
<p>See also video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a></p>
</section>
doc/pub/week38/html/week38-solarized.html
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@@ -238,7 +238,7 @@ MathJax.Hub.Config({
<ol>
<li> Statistical interpretation of Ridge and Lasso regression</li>
<li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff (this may partly be discussed during the exercise sessions as well.</li>
<li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/" target="_blank"><tt>https://youtu.be/</tt></a>
<li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a>
<!-- * <a href="https://youtu.be/omLmp_kkie0" target="_blank">Video of Lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember9.pdf" target="_blank">Whiteboard notes</a> --></li>
</ol>
@@ -1758,6 +1758,8 @@ the jupyter-notebook from week 37 (September 12-16).
</p>
<p>For the lab session, the following video on cross validation (from 2024), could be helpful, see <a href="https://www.youtube.com/watch?v=T9jjWsmsd1o" target="_blank"><tt>https://www.youtube.com/watch?v=T9jjWsmsd1o</tt></a></p>
<p>See also video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a></p>
<!-- ------------------- end of main content --------------- -->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2025, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
doc/pub/week38/html/week38.html
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@@ -315,7 +315,7 @@ MathJax.Hub.Config({
<ol>
<li> Statistical interpretation of Ridge and Lasso regression</li>
<li> Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff (this may partly be discussed during the exercise sessions as well.</li>
<li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/" target="_blank"><tt>https://youtu.be/</tt></a>
<li> The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a>
<!-- * <a href="https://youtu.be/omLmp_kkie0" target="_blank">Video of Lecture</a> -->
<!-- * <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember9.pdf" target="_blank">Whiteboard notes</a> --></li>
</ol>
@@ -1835,6 +1835,8 @@ the jupyter-notebook from week 37 (September 12-16).
</p>
<p>For the lab session, the following video on cross validation (from 2024), could be helpful, see <a href="https://www.youtube.com/watch?v=T9jjWsmsd1o" target="_blank"><tt>https://www.youtube.com/watch?v=T9jjWsmsd1o</tt></a></p>
<p>See also video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at <a href="https://youtu.be/J_41Hld6tTU" target="_blank"><tt>https://youtu.be/J_41Hld6tTU</tt></a></p>
<!-- ------------------- end of main content --------------- -->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2025, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
doc/pub/week38/ipynb/ipynb-week38-src.tar.gz
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doc/src/week38/week38.do.txt
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@@ -10,7 +10,7 @@ DATE: September 15-19, 2025
!bblock Material for the lecture on Monday September 15
o Statistical interpretation of Ridge and Lasso regression
o Resampling techniques, Bootstrap and cross validation and bias-variance tradeoff (this may partly be discussed during the exercise sessions as well.
o The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at URL:"https://youtu.be/"
o The material we did not cover last week, that is on more advanced methods for updating the learning rate, are covered by its own video. We will briefly discuss these topics at the beginning of the lecture and during the lab sessions. See video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at URL:"https://youtu.be/J_41Hld6tTU"
# * "Video of Lecture":"https://youtu.be/omLmp_kkie0"
# * "Whiteboard notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember9.pdf"
!eblock
@@ -1381,3 +1381,5 @@ the learning like ADAgrad, RMSprop and ADAM. As teaching material, see
the jupyter-notebook from week 37 (September 12-16).
For the lab session, the following video on cross validation (from 2024), could be helpful, see URL:"https://www.youtube.com/watch?v=T9jjWsmsd1o"
See also video on ADAgrad, RMSprop and ADAM (material from last week not covered during lecture) at URL:"https://youtu.be/J_41Hld6tTU"