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Morten Hjorth-Jensen
2023-05-30 21:56:08 +02:00
parent fe52f36a49
commit d091f89df6
7 changed files with 1193 additions and 653 deletions
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doc/pub/week39/html/week39-bs.html
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@@ -421,7 +421,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 1, 2022</h4>
<h4>Week 39</h4>
</center> <!-- date -->
<br>
@@ -460,7 +460,7 @@ MathJax.Hub.Config({
</footer>
-->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</body>
</html>
doc/pub/week39/html/week39-reveal.html
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@@ -184,13 +184,13 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 1, 2022</h4>
<h4>Week 39</h4>
</center> <!-- date -->
<br>
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</section>
@@ -198,18 +198,8 @@ MathJax.Hub.Config({
<h2 id="plan-for-week-39">Plan for week 39 </h2>
<ul>
<p><li> Thursday: Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of stochastic gradient descent</li>
<ul>
<p><li> <a href="https://youtu.be/rDBj50Lv3Go" target="_blank">Video of lecture</a></li>
</ul>
<p>
<p><li> Friday: Stochastic Gradient descent with examples and automatic differentiation</li>
<ul>
<p><li> <a href="https://youtu.be/OH6I_oscwPc" target="_blank">Video of lecture</a></li>
</ul>
<p>
<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 stochastic gradient descent</li>
<p><li> Stochastic Gradient descent with examples and automatic differentiation</li>
<p><li> Reading recommendations:</li>
</ul>
<p>
doc/pub/week39/html/week39-solarized.html
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@@ -335,7 +335,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 1, 2022</h4>
<h4>Week 39</h4>
</center> <!-- date -->
<br>
@@ -343,14 +343,8 @@ MathJax.Hub.Config({
<h2 id="plan-for-week-39">Plan for week 39 </h2>
<ul>
<li> Thursday: Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of stochastic gradient descent</li>
<ul>
<li> <a href="https://youtu.be/rDBj50Lv3Go" target="_blank">Video of lecture</a></li>
</ul>
<li> Friday: Stochastic Gradient descent with examples and automatic differentiation</li>
<ul>
<li> <a href="https://youtu.be/OH6I_oscwPc" target="_blank">Video of lecture</a></li>
</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 stochastic gradient descent</li>
<li> Stochastic Gradient descent with examples and automatic differentiation</li>
<li> Reading recommendations:</li>
</ul>
<p>See <a href="https://compphysics.github.io/MachineLearning/doc/web/course.html" target="_blank">lecture notes for week 39</a>.
@@ -3785,7 +3779,7 @@ derivative_fn = grad(sum_logistic)
<!-- ------------------- end of main content --------------- -->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</body>
</html>
doc/pub/week39/html/week39.html
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@@ -412,7 +412,7 @@ MathJax.Hub.Config({
</center>
<br>
<center>
<h4>Nov 1, 2022</h4>
<h4>Week 39</h4>
</center> <!-- date -->
<br>
@@ -420,14 +420,8 @@ MathJax.Hub.Config({
<h2 id="plan-for-week-39">Plan for week 39 </h2>
<ul>
<li> Thursday: Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of stochastic gradient descent</li>
<ul>
<li> <a href="https://youtu.be/rDBj50Lv3Go" target="_blank">Video of lecture</a></li>
</ul>
<li> Friday: Stochastic Gradient descent with examples and automatic differentiation</li>
<ul>
<li> <a href="https://youtu.be/OH6I_oscwPc" target="_blank">Video of lecture</a></li>
</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 stochastic gradient descent</li>
<li> Stochastic Gradient descent with examples and automatic differentiation</li>
<li> Reading recommendations:</li>
</ul>
<p>See <a href="https://compphysics.github.io/MachineLearning/doc/web/course.html" target="_blank">lecture notes for week 39</a>.
@@ -3862,7 +3856,7 @@ derivative_fn <span style="color: #666666">=</span> grad(sum_logistic)
<!-- ------------------- end of main content --------------- -->
<center style="font-size:80%">
<!-- copyright --> &copy; 1999-2022, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
<!-- copyright --> &copy; 1999-2023, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license
</center>
</body>
</html>
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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@@ -1,14 +1,13 @@
TITLE: Week 39: Optimization and Gradient Methods
AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of Physics, University of Oslo & Department of Physics and Astronomy and Facility for Rare Isotope Beams, Michigan State University
DATE: today
DATE: Week 39
!split
===== Plan for week 39 =====
* Thursday: Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of stochastic gradient descent
* "Video of lecture":"https://youtu.be/rDBj50Lv3Go"
* Friday: Stochastic Gradient descent with examples and automatic differentiation
* "Video of lecture":"https://youtu.be/OH6I_oscwPc"
* Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of stochastic gradient descent
* Stochastic Gradient descent with examples and automatic differentiation
* Reading recommendations:
See "lecture notes for week 39":"https://compphysics.github.io/MachineLearning/doc/web/course.html".