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small update on schedule

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Morten Hjorth-Jensen
2023-08-21 09:57:20 +02:00
parent 6caba02ac3
commit cc9c5de45b
4 changed files with 73 additions and 70 deletions
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doc/web/course.dlog
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@@ -231,3 +231,6 @@ 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
+14 -14
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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 22-26:Basic introduction to the course with schedule etc and start Linear Regression',
'week35': 'Week 35 August 29- September 2: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics',
'week36': 'Week 36 September 5-9: Statistical analysis and discussion of Ridge and Lasso regression',
'week37': 'Week 37 September 12-16: Resampling techniques, Cross-validation and the Bootstrap',
'week38': 'Week 38 September 19-23: Summary of linear regression methods and start Logistic Regression',
'week39': 'Week 39 September 26-30: Logistic Regression and Gradient methods',
'week40': 'Week 40 October 3-7: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm',
'week41': 'Week 41 October 10-14: Building a multi-layer perceptron code and introduction to Tensorflow',
'week42': 'Week 42 October 17-21: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks)',
'week43': 'Week 43 October 24-28: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks',
'week44': 'Week 44 October 31- November 4: Decision Trees and Ensemble models',
'week45': 'Week 45 November 7-11: Decision Trees, Random Forests and Gradient Boosting',
'week46': 'Week 46 November 14-18: Support Vector Machines',
'week47': 'Week 47 November 21-25: Support Vector Machines and unsupervised learning and Summary of Course with Future Perspectives',
'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',
'week40': 'Week 40 October 2-6: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm',
'week41': 'Week 41 October 9-13: Building a multi-layer perceptron code and introduction to Tensorflow',
'week42': 'Week 42 October 16-20: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks)',
'week43': 'Week 43 October 23-27: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks',
'week44': 'Week 44 October 30- November 3: Decision Trees and Ensemble models',
'week45': 'Week 45 November 6-10: Decision Trees, Random Forests and Gradient Boosting',
'week46': 'Week 46 November 13-17: Support Vector Machines',
'week47': 'Week 47 November 20-24: Support Vector Machines and unsupervised learning and Summary of Course with Future Perspectives',
}
%>
doc/web/course.html
+42 -42
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@@ -117,78 +117,78 @@ div.toc p,a {
<!-- tocinfo
{'highest level': 2,
'sections': [('Week 34 August 22-26:Basic introduction to the course with '
'sections': [('Week 34 August 21-25:Basic introduction to the course with '
'schedule etc and start Linear Regression',
2,
None,
'week-34-august-22-26-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression'),
('Week 35 August 29- September 2: Linear regression, from '
'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',
2,
None,
'week-35-august-29-september-2-linear-regression-from-ordinary-least-squares-to-ridge-and-lasso-regression-elements-of-statistics'),
('Week 36 September 5-9: Statistical analysis and discussion of '
'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 '
'Ridge and Lasso regression',
2,
None,
'week-36-september-5-9-statistical-analysis-and-discussion-of-ridge-and-lasso-regression'),
('Week 37 September 12-16: Resampling techniques, '
'week-36-september-4-8-statistical-analysis-and-discussion-of-ridge-and-lasso-regression'),
('Week 37 September 11-15: Resampling techniques, '
'Cross-validation and the Bootstrap',
2,
None,
'week-37-september-12-16-resampling-techniques-cross-validation-and-the-bootstrap'),
('Week 38 September 19-23: Summary of linear regression methods '
'week-37-september-11-15-resampling-techniques-cross-validation-and-the-bootstrap'),
('Week 38 September 18-22: Summary of linear regression methods '
'and start Logistic Regression',
2,
None,
'week-38-september-19-23-summary-of-linear-regression-methods-and-start-logistic-regression'),
('Week 39 September 26-30: Logistic Regression and Gradient '
'week-38-september-18-22-summary-of-linear-regression-methods-and-start-logistic-regression'),
('Week 39 September 25-29: Logistic Regression and Gradient '
'methods',
2,
None,
'week-39-september-26-30-logistic-regression-and-gradient-methods'),
('Week 40 October 3-7: Stochastic Gradient Descent and Neural '
'week-39-september-25-29-logistic-regression-and-gradient-methods'),
('Week 40 October 2-6: Stochastic Gradient Descent and Neural '
'Networks, starting to build a multi-layer Perceptron model, '
'the Back Propagation algoritm',
2,
None,
'week-40-october-3-7-stochastic-gradient-descent-and-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm'),
('Week 41 October 10-14: Building a multi-layer perceptron code '
'week-40-october-2-6-stochastic-gradient-descent-and-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm'),
('Week 41 October 9-13: Building a multi-layer perceptron code '
'and introduction to Tensorflow',
2,
None,
'week-41-october-10-14-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow'),
('Week 42 October 17-21: Deep learning, Solving Differential '
'week-41-october-9-13-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow'),
('Week 42 October 16-20: Deep learning, Solving Differential '
'Equations with NNs and Convolutional Neural Networks)',
2,
None,
'week-42-october-17-21-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks'),
('Week 43 October 24-28: Deep learning, Convolutional Neural '
'week-42-october-16-20-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks'),
('Week 43 October 23-27: Deep learning, Convolutional Neural '
'Networks and Recurrent Neural Networks',
2,
None,
'week-43-october-24-28-deep-learning-convolutional-neural-networks-and-recurrent-neural-networks'),
('Week 44 October 31- November 4: Decision Trees and Ensemble '
'week-43-october-23-27-deep-learning-convolutional-neural-networks-and-recurrent-neural-networks'),
('Week 44 October 30- November 3: Decision Trees and Ensemble '
'models',
2,
None,
'week-44-october-31-november-4-decision-trees-and-ensemble-models'),
('Week 45 November 7-11: Decision Trees, Random Forests and '
'week-44-october-30-november-3-decision-trees-and-ensemble-models'),
('Week 45 November 6-10: Decision Trees, Random Forests and '
'Gradient Boosting',
2,
None,
'week-45-november-7-11-decision-trees-random-forests-and-gradient-boosting'),
('Week 46 November 14-18: Support Vector Machines',
'week-45-november-6-10-decision-trees-random-forests-and-gradient-boosting'),
('Week 46 November 13-17: Support Vector Machines',
2,
None,
'week-46-november-14-18-support-vector-machines'),
('Week 47 November 21-25: Support Vector Machines and '
'week-46-november-13-17-support-vector-machines'),
('Week 47 November 20-24: Support Vector Machines and '
'unsupervised learning and Summary of Course with Future '
'Perspectives',
2,
None,
'week-47-november-21-25-support-vector-machines-and-unsupervised-learning-and-summary-of-course-with-future-perspectives'),
'week-47-november-20-24-support-vector-machines-and-unsupervised-learning-and-summary-of-course-with-future-perspectives'),
('Textbook', 2, None, 'textbook'),
('Projects Fall 2022 (dates are tentative)',
2,
@@ -228,7 +228,7 @@ 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-22-26-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression">Week 34 August 22-26:Basic introduction to the course with schedule etc and start Linear Regression </h2>
<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>
<ul>
<li> HTML:</li>
@@ -242,7 +242,7 @@ 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-29-september-2-linear-regression-from-ordinary-least-squares-to-ridge-and-lasso-regression-elements-of-statistics">Week 35 August 29- September 2: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression, Elements of Statistics </h2>
<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>
<ul>
<li> HTML:</li>
@@ -256,7 +256,7 @@ 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-5-9-statistical-analysis-and-discussion-of-ridge-and-lasso-regression">Week 36 September 5-9: Statistical analysis and discussion of Ridge and Lasso regression </h2>
<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>
<ul>
<li> HTML:</li>
@@ -270,7 +270,7 @@ 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-12-16-resampling-techniques-cross-validation-and-the-bootstrap">Week 37 September 12-16: Resampling techniques, Cross-validation and the Bootstrap </h2>
<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>
<ul>
<li> HTML:</li>
@@ -284,7 +284,7 @@ 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-19-23-summary-of-linear-regression-methods-and-start-logistic-regression">Week 38 September 19-23: Summary of linear regression methods and start Logistic Regression </h2>
<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>
<ul>
<li> HTML:</li>
@@ -298,7 +298,7 @@ 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-26-30-logistic-regression-and-gradient-methods">Week 39 September 26-30: Logistic Regression and Gradient methods </h2>
<h2 id="week-39-september-25-29-logistic-regression-and-gradient-methods">Week 39 September 25-29: Logistic Regression and Gradient methods </h2>
<ul>
<li> HTML:</li>
@@ -312,7 +312,7 @@ end of tocinfo -->
<li> <a href="https://compphysics.github.io/MachineLearning/doc/pub/week39/ipynb/week39.ipynb" target="_self">ipynb file</a></li>
</ul>
</ul>
<h2 id="week-40-october-3-7-stochastic-gradient-descent-and-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm">Week 40 October 3-7: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm </h2>
<h2 id="week-40-october-2-6-stochastic-gradient-descent-and-neural-networks-starting-to-build-a-multi-layer-perceptron-model-the-back-propagation-algoritm">Week 40 October 2-6: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm </h2>
<ul>
<li> HTML:</li>
@@ -326,7 +326,7 @@ 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-10-14-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow">Week 41 October 10-14: Building a multi-layer perceptron code and introduction to Tensorflow </h2>
<h2 id="week-41-october-9-13-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow">Week 41 October 9-13: Building a multi-layer perceptron code and introduction to Tensorflow </h2>
<ul>
<li> HTML:</li>
@@ -340,7 +340,7 @@ 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-17-21-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks">Week 42 October 17-21: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) </h2>
<h2 id="week-42-october-16-20-deep-learning-solving-differential-equations-with-nns-and-convolutional-neural-networks">Week 42 October 16-20: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) </h2>
<ul>
<li> HTML:</li>
@@ -354,7 +354,7 @@ 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-24-28-deep-learning-convolutional-neural-networks-and-recurrent-neural-networks">Week 43 October 24-28: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks </h2>
<h2 id="week-43-october-23-27-deep-learning-convolutional-neural-networks-and-recurrent-neural-networks">Week 43 October 23-27: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks </h2>
<ul>
<li> HTML:</li>
@@ -368,7 +368,7 @@ 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-31-november-4-decision-trees-and-ensemble-models">Week 44 October 31- November 4: Decision Trees and Ensemble models </h2>
<h2 id="week-44-october-30-november-3-decision-trees-and-ensemble-models">Week 44 October 30- November 3: Decision Trees and Ensemble models </h2>
<ul>
<li> HTML:</li>
@@ -382,7 +382,7 @@ 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-7-11-decision-trees-random-forests-and-gradient-boosting">Week 45 November 7-11: Decision Trees, Random Forests and Gradient Boosting </h2>
<h2 id="week-45-november-6-10-decision-trees-random-forests-and-gradient-boosting">Week 45 November 6-10: Decision Trees, Random Forests and Gradient Boosting </h2>
<ul>
<li> HTML:</li>
@@ -396,7 +396,7 @@ 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-14-18-support-vector-machines">Week 46 November 14-18: Support Vector Machines </h2>
<h2 id="week-46-november-13-17-support-vector-machines">Week 46 November 13-17: Support Vector Machines </h2>
<ul>
<li> HTML:</li>
@@ -410,7 +410,7 @@ 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-21-25-support-vector-machines-and-unsupervised-learning-and-summary-of-course-with-future-perspectives">Week 47 November 21-25: Support Vector Machines and unsupervised learning and Summary of Course with Future Perspectives </h2>
<h2 id="week-47-november-20-24-support-vector-machines-and-unsupervised-learning-and-summary-of-course-with-future-perspectives">Week 47 November 20-24: Support Vector Machines and unsupervised learning and Summary of Course with Future Perspectives </h2>
<ul>
<li> HTML:</li>
doc/web/tmp_mako__course.do.txt
+14 -14
View File
@@ -15,7 +15,7 @@ The teaching material is produced in various formats for running codes (jupyter
===== Week 34 August 22-26: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 =====
@@ -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 29- September 2: 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 =====
@@ -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 5-9: Statistical analysis and discussion of Ridge and Lasso regression =====
===== Week 36 September 4-8: 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 12-16: Resampling techniques, Cross-validation and the Bootstrap =====
===== Week 37 September 11-15: 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 19-23: Summary of linear regression methods and start Logistic Regression =====
===== Week 38 September 18-22: 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 26-30: Logistic Regression and Gradient methods =====
===== Week 39 September 25-29: 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 October 3-7: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm =====
===== Week 40 October 2-6: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model, the Back Propagation algoritm =====
@@ -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 10-14: Building a multi-layer perceptron code and introduction to Tensorflow =====
===== Week 41 October 9-13: Building a multi-layer perceptron code and introduction to Tensorflow =====
@@ -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 17-21: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) =====
===== Week 42 October 16-20: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks) =====
@@ -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 24-28: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks =====
===== Week 43 October 23-27: Deep learning, Convolutional Neural Networks and Recurrent 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 31- November 4: Decision Trees and Ensemble models =====
===== Week 44 October 30- November 3: Decision Trees and Ensemble models =====
@@ -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 7-11: Decision Trees, Random Forests and Gradient Boosting =====
===== Week 45 November 6-10: Decision Trees, Random Forests and Gradient Boosting =====
@@ -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 14-18: Support Vector Machines =====
===== Week 46 November 13-17: Support Vector Machines =====
@@ -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 21-25: Support Vector Machines and unsupervised learning and Summary of Course with Future Perspectives =====
===== Week 47 November 20-24: Support Vector Machines and unsupervised learning and Summary of Course with Future Perspectives =====