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Morten Hjorth-Jensen
2024-08-19 14:51:29 +02:00
parent aac7c1cac6
commit f46f97f041
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doc/web/course.dlog
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@@ -249,3 +249,6 @@ 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
+13 -13
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@@ -5,20 +5,20 @@ AUTHOR: "Morten Hjorth-Jensen":"http://mhjgit.github.io/info/doc/web/" at Depart
pub_url = 'https://compphysics.github.io/MachineLearning/doc/pub'
published = ['week34', 'week35', 'week36', 'week37', 'week38', 'week39', 'week40', 'week41', 'week42', 'week43', 'week44', 'week45', 'week46', 'week47', ]
chapters = {
'week34': 'Week 34 August 21-25:Basic introduction to the course with schedule etc and start Linear Regression',
'week35': 'Week 35 August 28- September 1: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics',
'week36': 'Week 36 September 4-8: Statistical analysis and discussion of Ridge and Lasso regression',
'week37': 'Week 37 September 11-15: Resampling techniques, Cross-validation and the Bootstrap',
'week38': 'Week 38 September 18-22: Summary of linear regression methods and start Logistic Regression',
'week39': 'Week 39 September 25-29: Logistic Regression and Gradient methods',
'week34': 'Week 34 August 19-23:Basic introduction to the course with schedule etc and start Linear Regression',
'week35': 'Week 35 August 26-30: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics',
'week36': 'Week 36 September 2-6: Statistical analysis and discussion of Ridge and Lasso regression',
'week37': 'Week 37 September 9-13: Resampling techniques, Cross-validation and the Bootstrap',
'week38': 'Week 38 September 16-20: Summary of linear regression methods and start Logistic Regression',
'week39': 'Week 39 September 23-27: Logistic Regression and Gradient methods',
'week40': 'Week 40 October 2-6: Stochastic Gradient Descent',
'week41': 'Week 41 October 9-13: Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm',
'week42': 'Week 42 October 16-20: Building a multi-layer perceptron code and introduction to Tensorflow',
'week43': 'Week 43 October 23-27: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks)',
'week44': 'Week 44 October 30- November 3: Convolutional Neural Networks',
'week45': 'Week 45 November 6-10: Convolutional neural networks and Recurrent neural networks',
'week46': 'Week 46 November 13-17: Decision trees, random forests and other ensemble methods',
'week47': 'Week 47 November 20-24: Ensemble methods, Bagging and Boosting and Summary of Course with Future Perspectives',
'week41': 'Week 41 October 7-11: Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm',
'week42': 'Week 42 October 14-18: Building a multi-layer perceptron code and introduction to Tensorflow',
'week43': 'Week 43 October 21-25: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks)',
'week44': 'Week 44 October 28- November 1: Convolutional Neural Networks',
'week45': 'Week 45 November 4-8: Convolutional neural networks and Recurrent neural networks',
'week46': 'Week 46 November 11-15: Decision trees, random forests and other ensemble methods',
'week47': 'Week 47 November 18-22: Ensemble methods, Bagging and Boosting and Summary of Course with Future Perspectives',
}
%>
doc/web/course.html
+40 -41
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@@ -117,75 +117,74 @@ div.toc p,a {
<!-- tocinfo
{'highest level': 2,
'sections': [('Week 34 August 21-25:Basic introduction to the course with '
'sections': [('Week 34 August 19-23:Basic introduction to the course with '
'schedule etc and start Linear Regression',
2,
None,
'week-34-august-21-25-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression'),
('Week 35 August 28- September 1: Linear regression, from '
'ordinary Least Squares to Ridge and Lasso Regression, Elements '
'of Statistics',
'week-34-august-19-23-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression'),
('Week 35 August 26-30: Linear regression, from ordinary Least '
'Squares to Ridge and Lasso Regression, Elements of Statistics',
2,
None,
'week-35-august-28-september-1-linear-regression-from-ordinary-least-squares-to-ridge-and-lasso-regression-elements-of-statistics'),
('Week 36 September 4-8: Statistical analysis and discussion of '
'week-35-august-26-30-linear-regression-from-ordinary-least-squares-to-ridge-and-lasso-regression-elements-of-statistics'),
('Week 36 September 2-6: Statistical analysis and discussion of '
'Ridge and Lasso regression',
2,
None,
'week-36-september-4-8-statistical-analysis-and-discussion-of-ridge-and-lasso-regression'),
('Week 37 September 11-15: Resampling techniques, '
'week-36-september-2-6-statistical-analysis-and-discussion-of-ridge-and-lasso-regression'),
('Week 37 September 9-13: Resampling techniques, '
'Cross-validation and the Bootstrap',
2,
None,
'week-37-september-11-15-resampling-techniques-cross-validation-and-the-bootstrap'),
('Week 38 September 18-22: Summary of linear regression methods '
'week-37-september-9-13-resampling-techniques-cross-validation-and-the-bootstrap'),
('Week 38 September 16-20: Summary of linear regression methods '
'and start Logistic Regression',
2,
None,
'week-38-september-18-22-summary-of-linear-regression-methods-and-start-logistic-regression'),
('Week 39 September 25-29: Logistic Regression and Gradient '
'week-38-september-16-20-summary-of-linear-regression-methods-and-start-logistic-regression'),
('Week 39 September 23-27: Logistic Regression and Gradient '
'methods',
2,
None,
'week-39-september-25-29-logistic-regression-and-gradient-methods'),
'week-39-september-23-27-logistic-regression-and-gradient-methods'),
('Week 40 October 2-6: Stochastic Gradient Descent',
2,
None,
'week-40-october-2-6-stochastic-gradient-descent'),
('Week 41 October 9-13: Neural Networks, starting to build a '
('Week 41 October 7-11: Neural Networks, starting to build a '
'multi-layer Perceptron model, the Back Propagation algoritm',
2,
None,
'week-41-october-9-13-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm'),
('Week 42 October 16-20: Building a multi-layer perceptron code '
'week-41-october-7-11-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm'),
('Week 42 October 14-18: Building a multi-layer perceptron code '
'and introduction to Tensorflow',
2,
None,
'week-42-october-16-20-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow'),
('Week 43 October 23-27: Deep learning, Solving Differential '
'week-42-october-14-18-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow'),
('Week 43 October 21-25: Deep learning, Solving Differential '
'Equations with NNs and Convolutional Neural Networks)',
2,
None,
'week-43-october-23-27-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks'),
('Week 44 October 30- November 3: Convolutional Neural Networks',
'week-43-october-21-25-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks'),
('Week 44 October 28- November 1: Convolutional Neural Networks',
2,
None,
'week-44-october-30-november-3-convolutional-neural-networks'),
('Week 45 November 6-10: Convolutional neural networks and '
'week-44-october-28-november-1-convolutional-neural-networks'),
('Week 45 November 4-8: Convolutional neural networks and '
'Recurrent neural networks',
2,
None,
'week-45-november-6-10-convolutional-neural-networks-and-recurrent-neural-networks'),
('Week 46 November 13-17: Decision trees, random forests and '
'week-45-november-4-8-convolutional-neural-networks-and-recurrent-neural-networks'),
('Week 46 November 11-15: Decision trees, random forests and '
'other ensemble methods',
2,
None,
'week-46-november-13-17-decision-trees-random-forests-and-other-ensemble-methods'),
('Week 47 November 20-24: Ensemble methods, Bagging and '
'week-46-november-11-15-decision-trees-random-forests-and-other-ensemble-methods'),
('Week 47 November 18-22: Ensemble methods, Bagging and '
'Boosting and Summary of Course with Future Perspectives',
2,
None,
'week-47-november-20-24-ensemble-methods-bagging-and-boosting-and-summary-of-course-with-future-perspectives'),
'week-47-november-18-22-ensemble-methods-bagging-and-boosting-and-summary-of-course-with-future-perspectives'),
('Textbook', 2, None, 'textbook'),
('Projects Fall 2023 (dates are tentative)',
2,
@@ -225,7 +224,7 @@ end of tocinfo -->
<br>
<p>The teaching material is produced in various formats for running codes (jupyter notebooks) and on-screen reading. Below you will also find a link to the lecture notes as a textbook in PDF format and as a jupyter notebook as well. Projects and exercise sets are also included.</p>
<h2 id="week-34-august-21-25-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression">Week 34 August 21-25:Basic introduction to the course with schedule etc and start Linear Regression </h2>
<h2 id="week-34-august-19-23-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression">Week 34 August 19-23:Basic introduction to the course with schedule etc and start Linear Regression </h2>
<ul>
<li> HTML:</li>
@@ -239,7 +238,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week34/ipynb/week34.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-35-august-28-september-1-linear-regression-from-ordinary-least-squares-to-ridge-and-lasso-regression-elements-of-statistics">Week 35 August 28- September 1: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics </h2>
<h2 id="week-35-august-26-30-linear-regression-from-ordinary-least-squares-to-ridge-and-lasso-regression-elements-of-statistics">Week 35 August 26-30: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics </h2>
<ul>
<li> HTML:</li>
@@ -253,7 +252,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week35/ipynb/week35.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-36-september-4-8-statistical-analysis-and-discussion-of-ridge-and-lasso-regression">Week 36 September 4-8: Statistical analysis and discussion of Ridge and Lasso regression </h2>
<h2 id="week-36-september-2-6-statistical-analysis-and-discussion-of-ridge-and-lasso-regression">Week 36 September 2-6: Statistical analysis and discussion of Ridge and Lasso regression </h2>
<ul>
<li> HTML:</li>
@@ -267,7 +266,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week36/ipynb/week36.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-37-september-11-15-resampling-techniques-cross-validation-and-the-bootstrap">Week 37 September 11-15: Resampling techniques, Cross-validation and the Bootstrap </h2>
<h2 id="week-37-september-9-13-resampling-techniques-cross-validation-and-the-bootstrap">Week 37 September 9-13: Resampling techniques, Cross-validation and the Bootstrap </h2>
<ul>
<li> HTML:</li>
@@ -281,7 +280,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week37/ipynb/week37.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-38-september-18-22-summary-of-linear-regression-methods-and-start-logistic-regression">Week 38 September 18-22: Summary of linear regression methods and start Logistic Regression </h2>
<h2 id="week-38-september-16-20-summary-of-linear-regression-methods-and-start-logistic-regression">Week 38 September 16-20: Summary of linear regression methods and start Logistic Regression </h2>
<ul>
<li> HTML:</li>
@@ -295,7 +294,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week38/ipynb/week38.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-39-september-25-29-logistic-regression-and-gradient-methods">Week 39 September 25-29: Logistic Regression and Gradient methods </h2>
<h2 id="week-39-september-23-27-logistic-regression-and-gradient-methods">Week 39 September 23-27: Logistic Regression and Gradient methods </h2>
<ul>
<li> HTML:</li>
@@ -323,7 +322,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week40/ipynb/week40.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-41-october-9-13-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm">Week 41 October 9-13: Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm </h2>
<h2 id="week-41-october-7-11-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm">Week 41 October 7-11: Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm </h2>
<ul>
<li> HTML:</li>
@@ -337,7 +336,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week41/ipynb/week41.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-42-october-16-20-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow">Week 42 October 16-20: Building a multi-layer perceptron code and introduction to Tensorflow </h2>
<h2 id="week-42-october-14-18-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow">Week 42 October 14-18: Building a multi-layer perceptron code and introduction to Tensorflow </h2>
<ul>
<li> HTML:</li>
@@ -351,7 +350,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week42/ipynb/week42.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-43-october-23-27-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks">Week 43 October 23-27: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) </h2>
<h2 id="week-43-october-21-25-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks">Week 43 October 21-25: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) </h2>
<ul>
<li> HTML:</li>
@@ -365,7 +364,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week43/ipynb/week43.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-44-october-30-november-3-convolutional-neural-networks">Week 44 October 30- November 3: Convolutional Neural Networks </h2>
<h2 id="week-44-october-28-november-1-convolutional-neural-networks">Week 44 October 28- November 1: Convolutional Neural Networks </h2>
<ul>
<li> HTML:</li>
@@ -379,7 +378,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week44/ipynb/week44.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-45-november-6-10-convolutional-neural-networks-and-recurrent-neural-networks">Week 45 November 6-10: Convolutional neural networks and Recurrent neural networks </h2>
<h2 id="week-45-november-4-8-convolutional-neural-networks-and-recurrent-neural-networks">Week 45 November 4-8: Convolutional neural networks and Recurrent neural networks </h2>
<ul>
<li> HTML:</li>
@@ -393,7 +392,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week45/ipynb/week45.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-46-november-13-17-decision-trees-random-forests-and-other-ensemble-methods">Week 46 November 13-17: Decision trees, random forests and other ensemble methods </h2>
<h2 id="week-46-november-11-15-decision-trees-random-forests-and-other-ensemble-methods">Week 46 November 11-15: Decision trees, random forests and other ensemble methods </h2>
<ul>
<li> HTML:</li>
@@ -407,7 +406,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week46/ipynb/week46.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-47-november-20-24-ensemble-methods-bagging-and-boosting-and-summary-of-course-with-future-perspectives">Week 47 November 20-24: Ensemble methods, Bagging and Boosting and Summary of Course with Future Perspectives </h2>
<h2 id="week-47-november-18-22-ensemble-methods-bagging-and-boosting-and-summary-of-course-with-future-perspectives">Week 47 November 18-22: Ensemble methods, Bagging and Boosting and Summary of Course with Future Perspectives </h2>
<ul>
<li> HTML:</li>
doc/web/tmp_mako__course.do.txt
+13 -13
View File
@@ -15,7 +15,7 @@ The teaching material is produced in various formats for running codes (jupyter
===== Week 34 August 21-25:Basic introduction to the course with schedule etc and start Linear Regression =====
===== Week 34 August 19-23:Basic introduction to the course with schedule etc and start Linear Regression =====
@@ -27,7 +27,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week34/ipynb/week34.ipynb"
===== Week 35 August 28- September 1: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics =====
===== Week 35 August 26-30: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics =====
@@ -39,7 +39,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week35/ipynb/week35.ipynb"
===== Week 36 September 4-8: Statistical analysis and discussion of Ridge and Lasso regression =====
===== Week 36 September 2-6: Statistical analysis and discussion of Ridge and Lasso regression =====
@@ -51,7 +51,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week36/ipynb/week36.ipynb"
===== Week 37 September 11-15: Resampling techniques, Cross-validation and the Bootstrap =====
===== Week 37 September 9-13: Resampling techniques, Cross-validation and the Bootstrap =====
@@ -63,7 +63,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week37/ipynb/week37.ipynb"
===== Week 38 September 18-22: Summary of linear regression methods and start Logistic Regression =====
===== Week 38 September 16-20: Summary of linear regression methods and start Logistic Regression =====
@@ -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 25-29: Logistic Regression and Gradient methods =====
===== Week 39 September 23-27: Logistic Regression and Gradient methods =====
@@ -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 9-13: Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm =====
===== Week 41 October 7-11: Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm =====
@@ -111,7 +111,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week41/ipynb/week41.ipynb"
===== Week 42 October 16-20: Building a multi-layer perceptron code and introduction to Tensorflow =====
===== Week 42 October 14-18: Building a multi-layer perceptron code and introduction to Tensorflow =====
@@ -123,7 +123,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week42/ipynb/week42.ipynb"
===== Week 43 October 23-27: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) =====
===== Week 43 October 21-25: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) =====
@@ -135,7 +135,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week43/ipynb/week43.ipynb"
===== Week 44 October 30- November 3: Convolutional Neural Networks =====
===== Week 44 October 28- November 1: Convolutional Neural Networks =====
@@ -147,7 +147,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week44/ipynb/week44.ipynb"
===== Week 45 November 6-10: Convolutional neural networks and Recurrent neural networks =====
===== Week 45 November 4-8: Convolutional neural networks and Recurrent neural networks =====
@@ -159,7 +159,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week45/ipynb/week45.ipynb"
===== Week 46 November 13-17: Decision trees, random forests and other ensemble methods =====
===== Week 46 November 11-15: Decision trees, random forests and other ensemble methods =====
@@ -171,7 +171,7 @@ The teaching material is produced in various formats for running codes (jupyter
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week46/ipynb/week46.ipynb"
===== Week 47 November 20-24: Ensemble methods, Bagging and Boosting and Summary of Course with Future Perspectives =====
===== Week 47 November 18-22: Ensemble methods, Bagging and Boosting and Summary of Course with Future Perspectives =====