diff --git a/doc/web/course.dlog b/doc/web/course.dlog
index ec2340005..b8b926661 100644
--- a/doc/web/course.dlog
+++ b/doc/web/course.dlog
@@ -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
diff --git a/doc/web/course.do.txt b/doc/web/course.do.txt
index e71c8516a..c02220f40 100644
--- a/doc/web/course.do.txt
+++ b/doc/web/course.do.txt
@@ -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',
 
 }
 %>
diff --git a/doc/web/course.html b/doc/web/course.html
index 1dc64319a..ca5c4d1de 100644
--- a/doc/web/course.html
+++ b/doc/web/course.html
@@ -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>
diff --git a/doc/web/tmp_mako__course.do.txt b/doc/web/tmp_mako__course.do.txt
index 2652a280f..d5d2eebe3 100644
--- a/doc/web/tmp_mako__course.do.txt
+++ b/doc/web/tmp_mako__course.do.txt
@@ -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 =====