diff --git a/doc/web/course.dlog b/doc/web/course.dlog
index e2300656c..0f28d0d12 100644
--- a/doc/web/course.dlog
+++ b/doc/web/course.dlog
@@ -171,3 +171,6 @@ 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 0a8955b0c..935fce90b 100644
--- a/doc/web/course.do.txt
+++ b/doc/web/course.do.txt
@@ -5,21 +5,21 @@ 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', 'week48', ]
 chapters = {
- 'week34': 'Week 34 August 17-21:Basic introduction to the course with schedule etc and start Linear Regression',
- 'week35': 'Week 35 August 24-28: Linear regression and review of statistics and probability theory',
- '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',
- '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',
- 'week45': 'Week 45 November 2-6: Random Forests and Gradient Boosting',
- 'week46': 'Week 46 November 9-13: Gradient boosting and Support Vector Machines',
- 'week47': 'Week 47 November 16-20: Support Vector Machines and Workshop on Project 3',
- 'week48': 'Week 48 November 23-27: Support Vector Machines and Summary of Course with Future Perspectives',
+ 'week34': 'Week 35 August 23-27:Basic introduction to the course with schedule etc and start Linear Regression',
+ 'week35': 'Week 36 August 30- September 3: Linear regression and review of statistics and probability theory',
+ 'week36': 'Week 37 September 6-10: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression',
+ 'week37': 'Week 38 September 13-17: Ridge and Lasso Regression',
+ 'week38': 'Week 39 September 20-24: Summary of linear regression methods and start Logistic Regression',
+ 'week39': 'Week 40 September 27- October 1: Logistic Regression and Gradient methods',
+ 'week40': 'Week 41 October 4-8: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model',
+ 'week41': 'Week 42 October 11-15: Building a multi-layer perceptron code and introduction to Tensorflow',
+ 'week42': 'Week 43 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks',
+ 'week43': 'Week 44 October 25-29: Dimesionality Reduction, Principal Component analysis',
+ 'week44': 'Week 45 November 1-5: Decision Trees and Bagging',
+ 'week45': 'Week 46 November 8-12: Random Forests and Gradient Boosting',
+ 'week46': 'Week 47 November 15-19: Gradient boosting and Support Vector Machines',
+ 'week47': 'Week 48 November 22-26: Support Vector Machines and Workshop on Project 3',
+ 'week48': 'Week 49 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives',
 
 }
 %>
@@ -64,7 +64,7 @@ ${text_types(ch)}
 
 
 !split
-===== Projects and Exercises Fall 2020 =====
+===== Projects and Exercises Fall 2021, to be updated =====
 
 === First homework set, week 35  ===
  * LaTeX and PDF:
diff --git a/doc/web/course.html b/doc/web/course.html
index 08d02763a..e9eea46b9 100644
--- a/doc/web/course.html
+++ b/doc/web/course.html
@@ -1,11 +1,11 @@
 <!--
 Automatically generated HTML file from DocOnce source
-(https://github.com/hplgit/doconce/)
+(https://github.com/doconce/doconce/)
 -->
 <html>
 <head>
 <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
-<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
+<meta name="generator" content="DocOnce: https://github.com/doconce/doconce/" />
 <meta name="viewport" content="width=device-width, initial-scale=1.0" />
 <meta name="description" content="Overview of course material: Data Analysis and Machine Learning (weekly schedule may be revised)">
 
@@ -15,8 +15,8 @@ Automatically generated HTML file from DocOnce source
 <style type="text/css">
 /* blueish style */
 
-/* Color definitions:  http://www.december.com/html/spec/color0.html
-   CSS examples:       http://www.w3schools.com/css/css_examples.asp */
+/* Color definitions:  https://www.december.com/html/spec/color0.html
+   CSS examples:       https://www.w3schools.com/css/css_examples.asp */
 
 body {
   margin-top: 1.0em;
@@ -43,96 +43,104 @@ div { text-align: justify; text-justify: inter-word; }
 
 <!-- tocinfo
 {'highest level': 2,
- 'sections': [('Week 34 August 17-21:Basic introduction to the course with '
+ 'sections': [('Week 35 August 23-27:Basic introduction to the course with '
                'schedule etc and start Linear Regression',
                2,
                None,
-               '___sec0'),
-              ('Week 35 August 24-28: Linear regression and review of '
-               'statistics and probability theory',
+               'week-35-august-23-27-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression'),
+              ('Week 36 August 30- September 3: Linear regression and review '
+               'of statistics and probability theory',
                2,
                None,
-               '___sec1'),
-              ('Week 36 August 31- September 4: Resampling techniques, '
+               'week-36-august-30-september-3-linear-regression-and-review-of-statistics-and-probability-theory'),
+              ('Week 37 September 6-10: Resampling techniques, '
                'Cross-validation and Bootstrap and start discussion of Ridge '
                'regression',
                2,
                None,
-               '___sec2'),
-              ('Week 37 September 7-11: Ridge and Lasso Regression',
+               'week-37-september-6-10-resampling-techniques-cross-validation-and-bootstrap-and-start-discussion-of-ridge-regression'),
+              ('Week 38 September 13-17: Ridge and Lasso Regression',
                2,
                None,
-               '___sec3'),
-              ('Week 38 September 14-18: Summary of linear regression methods '
+               'week-38-september-13-17-ridge-and-lasso-regression'),
+              ('Week 39 September 20-24: Summary of linear regression methods '
                'and start Logistic Regression',
                2,
                None,
-               '___sec4'),
-              ('Week 39 September 21-25: Logistic Regression and Gradient '
-               'methods',
+               'week-39-september-20-24-summary-of-linear-regression-methods-and-start-logistic-regression'),
+              ('Week 40 September 27- October 1: Logistic Regression and '
+               'Gradient methods',
                2,
                None,
-               '___sec5'),
-              ('Week 40 September 28 - October 2: Stochastic Gradient Descent '
-               'and Neural Networks, starting to build a multi-layer '
-               'Perceptron model',
+               'week-40-september-27-october-1-logistic-regression-and-gradient-methods'),
+              ('Week 41 October 4-8: Stochastic Gradient Descent and Neural '
+               'Networks, starting to build a multi-layer Perceptron model',
                2,
                None,
-               '___sec6'),
-              ('Week 41 October 5-9: Building a multi-layer perceptron code '
+               'week-41-october-4-8-stochastic-gradient-descent-and-neural-networks-starting-to-build-a-multi-layer-perceptron-model'),
+              ('Week 42 October 11-15: Building a multi-layer perceptron code '
                'and introduction to Tensorflow',
                2,
                None,
-               '___sec7'),
-              ('Week 42 October 12-16: Deep learning (Convolutional Neural '
+               'week-42-october-11-15-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow'),
+              ('Week 43 October 18-22: Deep learning (Convolutional Neural '
                'Networks and Recurrent Neural Networks',
                2,
                None,
-               '___sec8'),
-              ('Week 43 October 19-23: Dimesionality Reduction, Principal '
+               'week-43-october-18-22-deep-learning-convolutional-neural-networks-and-recurrent-neural-networks'),
+              ('Week 44 October 25-29: Dimesionality Reduction, Principal '
                'Component analysis',
                2,
                None,
-               '___sec9'),
-              ('Week 44 October 26-30: Decision Trees and Bagging',
+               'week-44-october-25-29-dimesionality-reduction-principal-component-analysis'),
+              ('Week 45 November 1-5: Decision Trees and Bagging',
                2,
                None,
-               '___sec10'),
-              ('Week 45 November 2-6: Random Forests and Gradient Boosting',
+               'week-45-november-1-5-decision-trees-and-bagging'),
+              ('Week 46 November 8-12: Random Forests and Gradient Boosting',
                2,
                None,
-               '___sec11'),
-              ('Week 46 November 9-13: Gradient boosting and Support Vector '
+               'week-46-november-8-12-random-forests-and-gradient-boosting'),
+              ('Week 47 November 15-19: Gradient boosting and Support Vector '
                'Machines',
                2,
                None,
-               '___sec12'),
-              ('Week 47 November 16-20: Support Vector Machines and Workshop '
+               'week-47-november-15-19-gradient-boosting-and-support-vector-machines'),
+              ('Week 48 November 22-26: Support Vector Machines and Workshop '
                'on Project 3',
                2,
                None,
-               '___sec13'),
-              ('Week 48 November 23-27: Support Vector Machines and Summary of '
-               'Course with Future Perspectives',
+               'week-48-november-22-26-support-vector-machines-and-workshop-on-project-3'),
+              ('Week 49 November 29- December 3: Support Vector Machines and '
+               'Summary of Course with Future Perspectives',
                2,
                None,
-               '___sec14'),
-              ('Textbook', 2, None, '___sec15'),
-              ('Projects and Exercises Fall 2020', 2, None, '___sec16'),
-              ('First homework set, week 35', 3, None, '___sec17'),
-              ('Second homework set, week 36', 3, None, '___sec18'),
+               'week-49-november-29-december-3-support-vector-machines-and-summary-of-course-with-future-perspectives'),
+              ('Textbook', 2, None, 'textbook'),
+              ('Projects and Exercises Fall 2021, to be updated',
+               2,
+               None,
+               'projects-and-exercises-fall-2021-to-be-updated'),
+              ('First homework set, week 35',
+               3,
+               None,
+               'first-homework-set-week-35'),
+              ('Second homework set, week 36',
+               3,
+               None,
+               'second-homework-set-week-36'),
               ('Project 1, Deadline October 10 (available September 1)',
                3,
                None,
-               '___sec19'),
+               'project-1-deadline-october-10-available-september-1'),
               ('Project 2, Deadline November 13 (available October 6)',
                3,
                None,
-               '___sec20'),
+               'project-2-deadline-november-13-available-october-6'),
               ('Project 3, Deadline December 16 (available November 9)',
                3,
                None,
-               '___sec21')]}
+               'project-3-deadline-december-16-available-november-9')]}
 end of tocinfo -->
 
 <body>
@@ -161,7 +169,7 @@ end of tocinfo -->
 <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.
 
-<h2 id="___sec0">Week 34 August 17-21:Basic introduction to the course with schedule etc and start Linear Regression </h2>
+<h2 id="week-35-august-23-27-basic-introduction-to-the-course-with-schedule-etc-and-start-linear-regression">Week 35 August 23-27:Basic introduction to the course with schedule etc and start Linear Regression </h2>
 
 <ul>
  <li> HTML:</li>
@@ -180,7 +188,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec1">Week 35 August 24-28: Linear regression and review of statistics and probability theory </h2>
+<h2 id="week-36-august-30-september-3-linear-regression-and-review-of-statistics-and-probability-theory">Week 36 August 30- September 3: Linear regression and review of statistics and probability theory </h2>
 
 <ul>
  <li> HTML:</li>
@@ -199,7 +207,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec2">Week 36 August 31- September 4: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression </h2>
+<h2 id="week-37-september-6-10-resampling-techniques-cross-validation-and-bootstrap-and-start-discussion-of-ridge-regression">Week 37 September 6-10: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression </h2>
 
 <ul>
  <li> HTML:</li>
@@ -218,7 +226,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec3">Week 37 September 7-11: Ridge and Lasso Regression </h2>
+<h2 id="week-38-september-13-17-ridge-and-lasso-regression">Week 38 September 13-17: Ridge and Lasso Regression </h2>
 
 <ul>
  <li> HTML:</li>
@@ -237,7 +245,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec4">Week 38 September 14-18: Summary of linear regression methods and start Logistic Regression </h2>
+<h2 id="week-39-september-20-24-summary-of-linear-regression-methods-and-start-logistic-regression">Week 39 September 20-24: Summary of linear regression methods and start Logistic Regression </h2>
 
 <ul>
  <li> HTML:</li>
@@ -256,7 +264,7 @@ 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 </h2>
+<h2 id="week-40-september-27-october-1-logistic-regression-and-gradient-methods">Week 40 September 27- October 1: Logistic Regression and Gradient methods </h2>
 
 <ul>
  <li> HTML:</li>
@@ -275,7 +283,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec6">Week 40 September 28 - October 2: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model </h2>
+<h2 id="week-41-october-4-8-stochastic-gradient-descent-and-neural-networks-starting-to-build-a-multi-layer-perceptron-model">Week 41 October 4-8: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model </h2>
 
 <ul>
  <li> HTML:</li>
@@ -294,7 +302,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec7">Week 41 October 5-9: Building a multi-layer perceptron code and introduction to Tensorflow </h2>
+<h2 id="week-42-october-11-15-building-a-multi-layer-perceptron-code-and-introduction-to-tensorflow">Week 42 October 11-15: Building a multi-layer perceptron code and introduction to Tensorflow </h2>
 
 <ul>
  <li> HTML:</li>
@@ -313,7 +321,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec8">Week 42 October 12-16: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks </h2>
+<h2 id="week-43-october-18-22-deep-learning-convolutional-neural-networks-and-recurrent-neural-networks">Week 43 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks </h2>
 
 <ul>
  <li> HTML:</li>
@@ -332,7 +340,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec9">Week 43 October 19-23: Dimesionality Reduction, Principal Component analysis </h2>
+<h2 id="week-44-october-25-29-dimesionality-reduction-principal-component-analysis">Week 44 October 25-29: Dimesionality Reduction, Principal Component analysis </h2>
 
 <ul>
  <li> HTML:</li>
@@ -351,7 +359,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec10">Week 44 October 26-30: Decision Trees and Bagging </h2>
+<h2 id="week-45-november-1-5-decision-trees-and-bagging">Week 45 November 1-5: Decision Trees and Bagging </h2>
 
 <ul>
  <li> HTML:</li>
@@ -370,7 +378,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec11">Week 45 November 2-6: Random Forests and Gradient Boosting </h2>
+<h2 id="week-46-november-8-12-random-forests-and-gradient-boosting">Week 46 November 8-12: Random Forests and Gradient Boosting </h2>
 
 <ul>
  <li> HTML:</li>
@@ -389,7 +397,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec12">Week 46 November 9-13: Gradient boosting and Support Vector Machines </h2>
+<h2 id="week-47-november-15-19-gradient-boosting-and-support-vector-machines">Week 47 November 15-19: Gradient boosting and Support Vector Machines </h2>
 
 <ul>
  <li> HTML:</li>
@@ -408,7 +416,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec13">Week 47 November 16-20: Support Vector Machines and Workshop on Project 3 </h2>
+<h2 id="week-48-november-22-26-support-vector-machines-and-workshop-on-project-3">Week 48 November 22-26: Support Vector Machines and Workshop on Project 3 </h2>
 
 <ul>
  <li> HTML:</li>
@@ -427,7 +435,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h2 id="___sec14">Week 48 November 23-27: Support Vector Machines and Summary of Course with Future Perspectives </h2>
+<h2 id="week-49-november-29-december-3-support-vector-machines-and-summary-of-course-with-future-perspectives">Week 49 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives </h2>
 
 <ul>
  <li> HTML:</li>
@@ -448,7 +456,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 <!-- !split -->
 
-<h2 id="___sec15">Textbook </h2>
+<h2 id="textbook">Textbook </h2>
 
 <ul>
  <li> PDF-file:</li>
@@ -467,9 +475,9 @@ The teaching material is produced in various formats for running codes (jupyter
 
 <!-- !split -->
 
-<h2 id="___sec16">Projects and Exercises Fall 2020 </h2>
+<h2 id="projects-and-exercises-fall-2021-to-be-updated">Projects and Exercises Fall 2021, to be updated </h2>
 
-<h3 id="___sec17">First homework set, week 35  </h3>
+<h3 id="first-homework-set-week-35">First homework set, week 35  </h3>
 
 <ul>
  <li> LaTeX and PDF:</li>
@@ -488,7 +496,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h3 id="___sec18">Second homework set, week 36  </h3>
+<h3 id="second-homework-set-week-36">Second homework set, week 36  </h3>
 
 <ul>
  <li> LaTeX and PDF:</li>
@@ -507,7 +515,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h3 id="___sec19">Project 1, Deadline October 10 (available September 1) </h3>
+<h3 id="project-1-deadline-october-10-available-september-1">Project 1, Deadline October 10 (available September 1) </h3>
 
 <ul>
  <li> LaTeX and PDF:</li>
@@ -532,7 +540,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h3 id="___sec20">Project 2, Deadline November 13 (available October 6) </h3>
+<h3 id="project-2-deadline-november-13-available-october-6">Project 2, Deadline November 13 (available October 6) </h3>
 
 <ul>
  <li> LaTeX and PDF:</li>
@@ -557,7 +565,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 </ul>
 
-<h3 id="___sec21">Project 3, Deadline December 16 (available November 9) </h3>
+<h3 id="project-3-deadline-december-16-available-november-9">Project 3, Deadline December 16 (available November 9) </h3>
 
 <ul>
  <li> LaTeX and PDF:</li>
diff --git a/doc/web/tmp_mako__course.do.txt b/doc/web/tmp_mako__course.do.txt
index 50065e93d..fbdcd1bba 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 17-21:Basic introduction to the course with schedule etc and start Linear Regression =====
+===== Week 35 August 23-27: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 24-28: Linear regression and review of statistics and probability theory =====
+===== Week 36 August 30- September 3: Linear regression and review of statistics and probability theory =====
 
 
 
@@ -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 August 31- September 4: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression =====
+===== Week 37 September 6-10: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge 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 7-11: Ridge and Lasso Regression =====
+===== Week 38 September 13-17: Ridge and Lasso Regression =====
 
 
 
@@ -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 14-18: Summary of linear regression methods and start Logistic Regression =====
+===== Week 39 September 20-24: 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 21-25: Logistic Regression and Gradient methods =====
+===== Week 40 September 27- October 1: 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: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model =====
+===== Week 41 October 4-8: 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: Building a multi-layer perceptron code and introduction to Tensorflow =====
+===== Week 42 October 11-15: 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 12-16: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks =====
+===== Week 43 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent 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 19-23: Dimesionality Reduction, Principal Component analysis =====
+===== Week 44 October 25-29: Dimesionality Reduction, Principal Component analysis =====
 
 
 
@@ -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 26-30: Decision Trees and Bagging =====
+===== Week 45 November 1-5: Decision Trees and Bagging =====
 
 
 
@@ -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 2-6: Random Forests and Gradient Boosting =====
+===== Week 46 November 8-12: 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 9-13: Gradient boosting and Support Vector Machines =====
+===== Week 47 November 15-19: Gradient boosting and 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 16-20: Support Vector Machines and Workshop on Project 3 =====
+===== Week 48 November 22-26: Support Vector Machines and Workshop on Project 3 =====
 
 
 
@@ -183,7 +183,7 @@ The teaching material is produced in various formats for running codes (jupyter
    * "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/week47/ipynb/week47.ipynb"
 
 
-===== Week 48 November 23-27: Support Vector Machines and Summary of Course with Future Perspectives =====
+===== Week 49 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives =====
 
 
 
@@ -208,7 +208,7 @@ The teaching material is produced in various formats for running codes (jupyter
 
 
 !split
-===== Projects and Exercises Fall 2020 =====
+===== Projects and Exercises Fall 2021, to be updated =====
 
 === First homework set, week 35  ===
  * LaTeX and PDF: