diff --git a/doc/web/course.dlog b/doc/web/course.dlog
index d06adc184..60f4a7773 100644
--- a/doc/web/course.dlog
+++ b/doc/web/course.dlog
@@ -183,3 +183,6 @@ Translating doconce text in tmp_mako__course.do.txt to 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 097606fb3..f3d5d4130 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 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',
+ 'week34': 'Week 34 August 23-27:Basic introduction to the course with schedule etc and start Linear Regression',
+ 'week35': 'Week 35 August 30- September 3: Linear regression and review of statistics and probability theory',
+ 'week36': 'Week 36 September 6-10: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression',
+ 'week37': 'Week 37 September 13-17: Ridge and Lasso Regression',
+ 'week38': 'Week 38 September 20-24: Summary of linear regression methods and start Logistic Regression',
+ 'week39': 'Week 39 September 27- October 1: Logistic Regression and Gradient methods',
+ 'week40': 'Week 40 October 4-8: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model',
+ 'week41': 'Week 41 October 11-15: Building a multi-layer perceptron code and introduction to Tensorflow',
+ 'week42': 'Week 42 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks',
+ 'week43': 'Week 43 October 25-29: Dimesionality Reduction, Principal Component analysis',
+ 'week44': 'Week 44 November 1-5: Decision Trees and Bagging',
+ 'week45': 'Week 45 November 8-12: Random Forests and Gradient Boosting',
+ 'week46': 'Week 46 November 15-19: Gradient boosting and Support Vector Machines',
+ 'week47': 'Week 47 November 22-26: Support Vector Machines and Workshop on Project 3',
+ 'week48': 'Week 48 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives',
}
%>
diff --git a/doc/web/course.html b/doc/web/course.html
index a33a4cb4e..a8d2bdda8 100644
--- a/doc/web/course.html
+++ b/doc/web/course.html
@@ -43,79 +43,79 @@ div { text-align: justify; text-justify: inter-word; }
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.
-
Week 35 August 23-27:Basic introduction to the course with schedule etc and start Linear Regression
+Week 34 August 23-27:Basic introduction to the course with schedule etc and start Linear Regression
- HTML:
@@ -180,7 +180,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 36 August 30- September 3: Linear regression and review of statistics and probability theory
+Week 35 August 30- September 3: Linear regression and review of statistics and probability theory
- HTML:
@@ -199,7 +199,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 37 September 6-10: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression
+Week 36 September 6-10: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression
- HTML:
@@ -218,7 +218,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 38 September 13-17: Ridge and Lasso Regression
+Week 37 September 13-17: Ridge and Lasso Regression
- HTML:
@@ -237,7 +237,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 39 September 20-24: Summary of linear regression methods and start Logistic Regression
+Week 38 September 20-24: Summary of linear regression methods and start Logistic Regression
- HTML:
@@ -256,7 +256,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 40 September 27- October 1: Logistic Regression and Gradient methods
+Week 39 September 27- October 1: Logistic Regression and Gradient methods
- HTML:
@@ -275,7 +275,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 41 October 4-8: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model
+Week 40 October 4-8: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model
- HTML:
@@ -294,7 +294,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 42 October 11-15: Building a multi-layer perceptron code and introduction to Tensorflow
+Week 41 October 11-15: Building a multi-layer perceptron code and introduction to Tensorflow
- HTML:
@@ -313,7 +313,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 43 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks
+Week 42 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks
- HTML:
@@ -332,7 +332,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 44 October 25-29: Dimesionality Reduction, Principal Component analysis
+Week 43 October 25-29: Dimesionality Reduction, Principal Component analysis
- HTML:
@@ -351,7 +351,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 45 November 1-5: Decision Trees and Bagging
+Week 44 November 1-5: Decision Trees and Bagging
- HTML:
@@ -370,7 +370,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 46 November 8-12: Random Forests and Gradient Boosting
+Week 45 November 8-12: Random Forests and Gradient Boosting
- HTML:
@@ -389,7 +389,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 47 November 15-19: Gradient boosting and Support Vector Machines
+Week 46 November 15-19: Gradient boosting and Support Vector Machines
- HTML:
@@ -408,7 +408,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 48 November 22-26: Support Vector Machines and Workshop on Project 3
+Week 47 November 22-26: Support Vector Machines and Workshop on Project 3
- HTML:
@@ -427,7 +427,7 @@ The teaching material is produced in various formats for running codes (jupyter
-Week 49 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives
+Week 48 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives
- HTML:
diff --git a/doc/web/tmp_mako__course.do.txt b/doc/web/tmp_mako__course.do.txt
index e2734bba0..dfe16167d 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 35 August 23-27:Basic introduction to the course with schedule etc and start Linear Regression =====
+===== Week 34 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 36 August 30- September 3: Linear regression and review of statistics and probability theory =====
+===== Week 35 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 37 September 6-10: Resampling techniques, Cross-validation and Bootstrap and start discussion of Ridge regression =====
+===== Week 36 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 38 September 13-17: Ridge and Lasso Regression =====
+===== Week 37 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 39 September 20-24: Summary of linear regression methods and start Logistic Regression =====
+===== Week 38 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 40 September 27- October 1: Logistic Regression and Gradient methods =====
+===== Week 39 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 41 October 4-8: Stochastic Gradient Descent and Neural Networks, starting to build a multi-layer Perceptron model =====
+===== Week 40 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 42 October 11-15: Building a multi-layer perceptron code and introduction to Tensorflow =====
+===== Week 41 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 43 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks =====
+===== Week 42 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 44 October 25-29: Dimesionality Reduction, Principal Component analysis =====
+===== Week 43 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 45 November 1-5: Decision Trees and Bagging =====
+===== Week 44 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 46 November 8-12: Random Forests and Gradient Boosting =====
+===== Week 45 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 47 November 15-19: Gradient boosting and Support Vector Machines =====
+===== Week 46 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 48 November 22-26: Support Vector Machines and Workshop on Project 3 =====
+===== Week 47 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 49 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives =====
+===== Week 48 November 29- December 3: Support Vector Machines and Summary of Course with Future Perspectives =====