diff --git a/doc/web/course.dlog b/doc/web/course.dlog
index ef9845192..8ebfb5b42 100644
--- a/doc/web/course.dlog
+++ b/doc/web/course.dlog
@@ -204,3 +204,6 @@ 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 a2e132e76..db623c225 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 23-27:Basic introduction to the course with schedule etc and start Linear Regression',
- 'week35': 'Week 35 August 30- September 3: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression',
- 'week36': 'Week 36 September 6-10: Statistical analysis and discussion of Ridge and Lasso regression',
- 'week37': 'Week 37 September 13-17: Resampling techniques, Cross-validation and the Bootstrap',
- '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, the Back Propagation algoritm',
- 'week41': 'Week 41 October 11-15: Building a multi-layer perceptron code and introduction to Tensorflow',
- 'week42': 'Week 42 October 18-22: Deep learning, Solving Differential Equations with NNs and Convolutional Neural Networks)',
- 'week43': 'Week 43 October 25-29: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks, Principal Component Analysis',
- 'week44': 'Week 44 November 1-5: Principal Component analysis, Clustering and Decision Trees',
- 'week45': 'Week 45 November 8-12: Decision Trees, 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 Summary of Course with Future Perspectives',
+ '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',
+ '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, Principal Component Analysis',
+ 'week44': 'Week 44 October 31- November 4: Principal Component analysis, Clustering and Decision Trees',
+ 'week45': 'Week 45 November 7-11: Decision Trees, Random Forests and Gradient Boosting',
+ 'week46': 'Week 46 November 14-18: Gradient boosting and Support Vector Machines',
+ 'week47': 'Week 47 November 21-25: Support Vector Machines and Summary of Course with Future Perspectives',
}
%>
@@ -63,39 +63,39 @@ ${text_types(ch)}
!split
-===== Projects Fall 2021 (dates are tentative) =====
+===== Projects Fall 2022 (dates are tentative) =====
-=== Project 1, Deadline October 11 (available September 10) ===
+=== Project 1, Deadline October 7 (available September 3) ===
* LaTeX and PDF:
- * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/pdf/Project1.tex"
- * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/pdf/Project1.pdf"
+ * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/pdf/Project1.tex"
+ * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/pdf/Project1.pdf"
* HTML:
- * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/html/Project1.html"
- * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/html/Project1-bs.html"
+ * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/html/Project1.html"
+ * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/html/Project1-bs.html"
* Jupyter notebook:
- * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/ipynb/Project1.ipynb"
+ * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/ipynb/Project1.ipynb"
-=== Project 2, Deadline November 20 (available October 12) ===
+=== Project 2, Deadline November 11 (available October 7) ===
* LaTeX and PDF:
- * "Latex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/pdf/Project2.tex"
- * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/pdf/Project2.pdf"
+ * "Latex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/pdf/Project2.tex"
+ * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/pdf/Project2.pdf"
* HTML:
- * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/html/Project2.html"
- * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/html/Project2-bs.html"
+ * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/html/Project2.html"
+ * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/html/Project2-bs.html"
* Jupyter notebook:
- * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/ipynb/Project2.ipynb"
+ * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/ipynb/Project2.ipynb"
-=== Project 3, Deadline December 17 (available November 13) ===
+=== Project 3, Deadline December 9 (available November 11) ===
* LaTeX and PDF:
- * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/pdf/Project3.tex"
- * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/pdf/Project3.pdf"
+ * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/pdf/Project3.tex"
+ * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/pdf/Project3.pdf"
* HTML:
- * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/html/Project3.html"
- * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/html/Project3-bs.html"
+ * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/html/Project3.html"
+ * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/html/Project3-bs.html"
* Jupyter notebook:
- * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/ipynb/Project3.ipynb"
+ * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/ipynb/Project3.ipynb"
diff --git a/doc/web/course.html b/doc/web/course.html
index a7b15a37a..99e7e2c3e 100644
--- a/doc/web/course.html
+++ b/doc/web/course.html
@@ -117,95 +117,95 @@ div.toc p,a {
@@ -228,7 +228,7 @@ end of tocinfo -->
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 34 August 23-27: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
- HTML:
@@ -242,7 +242,7 @@ end of tocinfo -->
- ipynb file
-Week 35 August 30- September 3: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression
+Week 35 August 29- September 2: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression
- HTML:
@@ -256,7 +256,7 @@ end of tocinfo -->
- ipynb file
-Week 36 September 6-10: Statistical analysis and discussion of Ridge and Lasso regression
+Week 36 September 5-9: Statistical analysis and discussion of Ridge and Lasso regression
- HTML:
@@ -270,7 +270,7 @@ end of tocinfo -->
- ipynb file
-Week 37 September 13-17: Resampling techniques, Cross-validation and the Bootstrap
+Week 37 September 12-16: Resampling techniques, Cross-validation and the Bootstrap
- HTML:
@@ -284,7 +284,7 @@ end of tocinfo -->
- ipynb file
-Week 38 September 20-24: Summary of linear regression methods and start Logistic Regression
+Week 38 September 19-23: Summary of linear regression methods and start Logistic Regression
- HTML:
@@ -298,7 +298,7 @@ end of tocinfo -->
- ipynb file
-Week 39 September 27- October 1: Logistic Regression and Gradient methods
+Week 39 September 26-30: Logistic Regression and Gradient methods
- HTML:
@@ -312,7 +312,7 @@ end of tocinfo -->
- ipynb file
-Week 40 October 4-8: 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
- HTML:
@@ -326,7 +326,7 @@ end of tocinfo -->
- ipynb file
-Week 41 October 11-15: 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
- HTML:
@@ -340,7 +340,7 @@ end of tocinfo -->
- ipynb file
-Week 42 October 18-22: 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)
- HTML:
@@ -354,7 +354,7 @@ end of tocinfo -->
- ipynb file
-Week 43 October 25-29: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks, Principal Component Analysis
+Week 43 October 24-28: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks, Principal Component Analysis
- HTML:
@@ -368,7 +368,7 @@ end of tocinfo -->
- ipynb file
-Week 44 November 1-5: Principal Component analysis, Clustering and Decision Trees
+Week 44 October 31- November 4: Principal Component analysis, Clustering and Decision Trees
- HTML:
@@ -382,7 +382,7 @@ end of tocinfo -->
- ipynb file
-Week 45 November 8-12: Decision Trees, Random Forests and Gradient Boosting
+Week 45 November 7-11: Decision Trees, Random Forests and Gradient Boosting
- HTML:
@@ -396,7 +396,7 @@ end of tocinfo -->
- ipynb file
-Week 46 November 15-19: Gradient boosting and Support Vector Machines
+Week 46 November 14-18: Gradient boosting and Support Vector Machines
- HTML:
@@ -410,7 +410,7 @@ end of tocinfo -->
- ipynb file
-Week 47 November 22-26: Support Vector Machines and Summary of Course with Future Perspectives
+Week 47 November 21-25: Support Vector Machines and Summary of Course with Future Perspectives
- HTML:
@@ -437,56 +437,56 @@ end of tocinfo -->
-Projects Fall 2021 (dates are tentative)
-Project 1, Deadline October 11 (available September 10)
+Projects Fall 2022 (dates are tentative)
+Project 1, Deadline October 7 (available September 3)
- LaTeX and PDF:
- HTML:
- Jupyter notebook:
-Project 2, Deadline November 20 (available October 12)
+Project 2, Deadline November 11 (available October 7)
- LaTeX and PDF:
- HTML:
- Jupyter notebook:
-Project 3, Deadline December 17 (available November 13)
+Project 3, Deadline December 9 (available November 11)
- LaTeX and PDF:
- HTML:
- Jupyter notebook:
diff --git a/doc/web/tmp_mako__course.do.txt b/doc/web/tmp_mako__course.do.txt
index 2a1238eae..afb8cd481 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 23-27: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 =====
@@ -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 30- September 3: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression =====
+===== Week 35 August 29- September 2: Linear regression, from ordinary Least Squares to Ridge and Lasso Regression =====
@@ -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 6-10: Statistical analysis and discussion of Ridge and Lasso regression =====
+===== Week 36 September 5-9: 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 13-17: Resampling techniques, Cross-validation and the Bootstrap =====
+===== Week 37 September 12-16: 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 20-24: Summary of linear regression methods and start Logistic Regression =====
+===== Week 38 September 19-23: 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 27- October 1: Logistic Regression and Gradient methods =====
+===== Week 39 September 26-30: 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 4-8: 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 =====
@@ -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 11-15: 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 =====
@@ -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 18-22: 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) =====
@@ -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 25-29: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks, Principal Component Analysis =====
+===== Week 43 October 24-28: Deep learning, Convolutional Neural Networks and Recurrent Neural Networks, 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 November 1-5: Principal Component analysis, Clustering and Decision Trees =====
+===== Week 44 October 31- November 4: Principal Component analysis, Clustering and Decision Trees =====
@@ -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 8-12: Decision Trees, Random Forests and Gradient Boosting =====
+===== Week 45 November 7-11: 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 15-19: Gradient boosting and Support Vector Machines =====
+===== Week 46 November 14-18: 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 22-26: Support Vector Machines and Summary of Course with Future Perspectives =====
+===== Week 47 November 21-25: Support Vector Machines and Summary of Course with Future Perspectives =====
@@ -196,39 +196,39 @@ The teaching material is produced in various formats for running codes (jupyter
!split
-===== Projects Fall 2021 (dates are tentative) =====
+===== Projects Fall 2022 (dates are tentative) =====
-=== Project 1, Deadline October 11 (available September 10) ===
+=== Project 1, Deadline October 7 (available September 3) ===
* LaTeX and PDF:
- * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/pdf/Project1.tex"
- * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/pdf/Project1.pdf"
+ * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/pdf/Project1.tex"
+ * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/pdf/Project1.pdf"
* HTML:
- * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/html/Project1.html"
- * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/html/Project1-bs.html"
+ * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/html/Project1.html"
+ * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/html/Project1-bs.html"
* Jupyter notebook:
- * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/ipynb/Project1.ipynb"
+ * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project1/ipynb/Project1.ipynb"
-=== Project 2, Deadline November 20 (available October 12) ===
+=== Project 2, Deadline November 11 (available October 7) ===
* LaTeX and PDF:
- * "Latex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/pdf/Project2.tex"
- * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/pdf/Project2.pdf"
+ * "Latex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/pdf/Project2.tex"
+ * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/pdf/Project2.pdf"
* HTML:
- * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/html/Project2.html"
- * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/html/Project2-bs.html"
+ * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/html/Project2.html"
+ * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/html/Project2-bs.html"
* Jupyter notebook:
- * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/ipynb/Project2.ipynb"
+ * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project2/ipynb/Project2.ipynb"
-=== Project 3, Deadline December 17 (available November 13) ===
+=== Project 3, Deadline December 9 (available November 11) ===
* LaTeX and PDF:
- * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/pdf/Project3.tex"
- * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/pdf/Project3.pdf"
+ * "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/pdf/Project3.tex"
+ * "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/pdf/Project3.pdf"
* HTML:
- * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/html/Project3.html"
- * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/html/Project3-bs.html"
+ * "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/html/Project3.html"
+ * "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/html/Project3-bs.html"
* Jupyter notebook:
- * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/ipynb/Project3.ipynb"
+ * "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2022/Project3/ipynb/Project3.ipynb"