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Merge branch 'master' of https://github.com/CompPhysics/MachineLearning

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Morten Hjorth-Jensen
2020-10-01 14:51:26 +02:00
parent 26461563c0 8ae6436fcd
commit cf97251083
14 changed files with 42 additions and 39 deletions
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doc/pub/week40/html/._week40-bs000.html
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@@ -254,7 +254,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Sep 29, 2020</h4></center> <!-- date -->
<center><h4>Sep 30, 2020</h4></center> <!-- date -->
<br>
<p>
doc/pub/week40/html/._week40-bs001.html
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@@ -238,8 +238,8 @@ MathJax.Hub.Config({
<h2 id="___sec0" class="anchor">Plan for week 40 </h2>
<ul>
<li> Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks</li>
<li> Friday: Neural Networks, setting up the basic steps</li>
<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks</li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
</ul>
Reading suggestions for both days: <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_self">Aurelien Geron's chapter 10</a> and Hastie et al chapter 11.
doc/pub/week40/html/._week40-bs002.html
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@@ -238,7 +238,7 @@ MathJax.Hub.Config({
<h2 id="___sec1" class="anchor">Overview video for week 40 </h2>
<p>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage" target="_self">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverviewWeek40.mp4?vrtx=view-as-webpage" target="_self">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
<p>
<p>
doc/pub/week40/html/week40-bs.html
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@@ -254,7 +254,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Sep 29, 2020</h4></center> <!-- date -->
<center><h4>Sep 30, 2020</h4></center> <!-- date -->
<br>
<p>
doc/pub/week40/html/week40-reveal.html
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@@ -148,7 +148,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>&nbsp;<br>
<center><h4>Sep 29, 2020</h4></center> <!-- date -->
<center><h4>Sep 30, 2020</h4></center> <!-- date -->
<br>
<p>
@@ -162,8 +162,8 @@ MathJax.Hub.Config({
<h2 id="___sec0">Plan for week 40 </h2>
<ul>
<p><li> Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks</li>
<p><li> Friday: Neural Networks, setting up the basic steps</li>
<p><li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks</li>
<p><li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
</ul>
<p>
@@ -176,7 +176,7 @@ For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
<h2 id="___sec1">Overview video for week 40 </h2>
<p>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage" target="_blank">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverviewWeek40.mp4?vrtx=view-as-webpage" target="_blank">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
</section>
doc/pub/week40/html/week40-solarized.html
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@@ -186,7 +186,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Sep 29, 2020</h4></center> <!-- date -->
<center><h4>Sep 30, 2020</h4></center> <!-- date -->
<br>
<p>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -194,8 +194,8 @@ MathJax.Hub.Config({
<h2 id="___sec0">Plan for week 40 </h2>
<ul>
<li> Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks</li>
<li> Friday: Neural Networks, setting up the basic steps</li>
<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks</li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
</ul>
Reading suggestions for both days: <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapter 10</a> and Hastie et al chapter 11.
@@ -207,7 +207,7 @@ For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
<h2 id="___sec1">Overview video for week 40 </h2>
<p>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage" target="_blank">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverviewWeek40.mp4?vrtx=view-as-webpage" target="_blank">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
<p>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
doc/pub/week40/html/week40.html
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@@ -191,7 +191,7 @@ MathJax.Hub.Config({
<center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
<br>
<p>
<center><h4>Sep 29, 2020</h4></center> <!-- date -->
<center><h4>Sep 30, 2020</h4></center> <!-- date -->
<br>
<p>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -199,8 +199,8 @@ MathJax.Hub.Config({
<h2 id="___sec0">Plan for week 40 </h2>
<ul>
<li> Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks</li>
<li> Friday: Neural Networks, setting up the basic steps</li>
<li> Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks</li>
<li> Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model</li>
</ul>
Reading suggestions for both days: <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" target="_blank">Aurelien Geron's chapter 10</a> and Hastie et al chapter 11.
@@ -212,7 +212,7 @@ For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
<h2 id="___sec1">Overview video for week 40 </h2>
<p>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage" target="_blank">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
<a href="https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverviewWeek40.mp4?vrtx=view-as-webpage" target="_blank">Overview Video, from Stochastic Gradient methods to Neural Networks</a>
<p>
<!-- !split --><br><br><br><br><br><br><br><br><br><br>
doc/pub/week40/ipynb/ipynb-week40-src.tar.gz
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doc/pub/week40/ipynb/week40.ipynb
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@@ -10,7 +10,7 @@
"<!-- Author: --> \n",
"**Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\n",
"\n",
"Date: **Sep 29, 2020**\n",
"Date: **Sep 30, 2020**\n",
"\n",
"Copyright 1999-2020, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n",
"\n",
@@ -19,16 +19,16 @@
"\n",
"## Plan for week 40\n",
"\n",
"* Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks \n",
"* Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks \n",
"\n",
"* Friday: Neural Networks, setting up the basic steps\n",
"* Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model\n",
"\n",
"Reading suggestions for both days: [Aurelien Geron's chapter 10](https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf) and Hastie et al chapter 11.\n",
"For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text. \n",
"\n",
"## Overview video for week 40\n",
"\n",
"[Overview Video, from Stochastic Gradient methods to Neural Networks](https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage)\n",
"[Overview Video, from Stochastic Gradient methods to Neural Networks](https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverviewWeek40.mp4?vrtx=view-as-webpage)\n",
"\n",
"## Stochastic Gradient Descent\n",
"\n",
doc/src/week40/week40.do.txt
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@@ -6,8 +6,8 @@ DATE: today
!split
===== Plan for week 40 =====
* Thursday: Stochastic Gradient descent with examples and automatic differeantion and begin Neural Networks
* Friday: Neural Networks, setting up the basic steps
* Thursday: Stochastic Gradient descent with examples and automatic differentiation and begin Neural Networks
* Friday: Neural Networks, setting up the basic steps, from the simple perceptron model to the multi-layer perceptron model
Reading suggestions for both days: "Aurelien Geron's chapter 10":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/Textbooks/TensorflowML.pdf" and Hastie et al chapter 11.
For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
@@ -15,7 +15,7 @@ For Stochastic Gradient Descent, we recommend chapter 4 of Geron's text.
!split
===== Overview video for week 40 =====
"Overview Video, from Stochastic Gradient methods to Neural Networks":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverarchingAimsWeek40.mp4?vrtx=view-as-webpage"
"Overview Video, from Stochastic Gradient methods to Neural Networks":"https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h20/forelesningsvideoer/OverviewWeek40.mp4?vrtx=view-as-webpage"
!split
===== Stochastic Gradient Descent =====
doc/web/course.dlog
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@@ -147,3 +147,6 @@ output in course.html
running mako on course.do.txt to make tmp_mako__course.do.txt
translating doconce text in tmp_mako__course.do.txt to html
output in course.html
running mako on course.do.txt to make tmp_mako__course.do.txt
translating doconce text in tmp_mako__course.do.txt to html
output in course.html
doc/web/course.do.txt
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@@ -10,9 +10,9 @@ chapters = {
'week36': 'Week 36 August 31- September 4: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression',
'week37': 'Week 37 September 7-11: Ridge and Lasso Regression',
'week38': 'Week 38 September 14-18: Summary of linear regression methods and start Logistic Regression',
'week39': 'Week 39 September 21-25: Logistic Regression and Gradient methods. Start Neural Networks',
'week40': 'Week 40 September 28 - October 2: Neural Networks, building a multi-layer Perceptron model',
'week41': 'Week 41 October 5-9: Introduction to Tensorflow and deep learning (Convolutional Neural Networks and Recurrent Neural Networks)',
'week39': 'Week 39 September 21-25: Logistic Regression and Gradient methods',
'week40': 'Week 40 September 28 - October 2: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model',
'week41': 'Week 41 October 5-9: Building a multi-layer perceptron code and introduction to Tensorflow',
'week42': 'Week 42 October 12-16: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks',
'week43': 'Week 43 October 19-23: Dimesionality Reduction, Principal Component analysis',
'week44': 'Week 44 October 26-30: Decision Trees and Bagging',
doc/web/course.html
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@@ -69,18 +69,18 @@ div { text-align: justify; text-justify: inter-word; }
None,
'___sec4'),
('Week 39 September 21-25: Logistic Regression and Gradient '
'methods. Start Neural Networks',
'methods',
2,
None,
'___sec5'),
('Week 40 September 28 - October 2: Neural Networks, building a '
'multi-layer Perceptron model',
('Week 40 September 28 - October 2: Stochastic Gradient Descent '
'and Neural Networks, starting to build a multi-layer '
'Perceptron model',
2,
None,
'___sec6'),
('Week 41 October 5-9: Introduction to Tensorflow and deep '
'learning (Convolutional Neural Networks and Recurrent Neural '
'Networks)',
('Week 41 October 5-9: Building a multi-layer perceptron code '
'and introduction to Tensorflow',
2,
None,
'___sec7'),
@@ -254,7 +254,7 @@ The teaching material is produced in various formats for running codes (jupyter
</ul>
<h2 id="___sec5">Week 39 September 21-25: Logistic Regression and Gradient methods. Start Neural Networks </h2>
<h2 id="___sec5">Week 39 September 21-25: Logistic Regression and Gradient methods </h2>
<ul>
<li> HTML:</li>
@@ -273,7 +273,7 @@ The teaching material is produced in various formats for running codes (jupyter
</ul>
<h2 id="___sec6">Week 40 September 28 - October 2: Neural Networks, building a multi-layer Perceptron model </h2>
<h2 id="___sec6">Week 40 September 28 - October 2: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model </h2>
<ul>
<li> HTML:</li>
@@ -292,7 +292,7 @@ The teaching material is produced in various formats for running codes (jupyter
</ul>
<h2 id="___sec7">Week 41 October 5-9: Introduction to Tensorflow and deep learning (Convolutional Neural Networks and Recurrent Neural Networks) </h2>
<h2 id="___sec7">Week 41 October 5-9: Building a multi-layer perceptron code and introduction to Tensorflow </h2>
<ul>
<li> HTML:</li>
doc/web/tmp_mako__course.do.txt
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@@ -75,7 +75,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week38/ipynb/week38.ipynb"
===== Week 39 September 21-25: Logistic Regression and Gradient methods. Start Neural Networks =====
===== Week 39 September 21-25: Logistic Regression and Gradient methods =====
@@ -87,7 +87,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week39/ipynb/week39.ipynb"
===== Week 40 September 28 - October 2: Neural Networks, building a multi-layer Perceptron model =====
===== Week 40 September 28 - October 2: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model =====
@@ -99,7 +99,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week40/ipynb/week40.ipynb"
===== Week 41 October 5-9: Introduction to Tensorflow and deep learning (Convolutional Neural Networks and Recurrent Neural Networks) =====
===== Week 41 October 5-9: Building a multi-layer perceptron code and introduction to Tensorflow =====