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FYS-STK4155/doc/web/course.do.txt
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Morten Hjorth-Jensen 74fd3a2dca updating web site
2021-09-08 06:14:38 +02:00

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TITLE: Overview of course material: Data Analysis and Machine Learning (weekly schedule may be revised)
AUTHOR: "Morten Hjorth-Jensen":"http://mhjgit.github.io/info/doc/web/" at Department of Physics and Astronomy and Facility for Rare ion Beams and National Superconducting Cyclotron Laboratory, Michigan State University, USA & Department of Physics and Center for Computing in Science Education (office FØ470), University of Oslo, Norway
<%
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 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',
'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',
}
%>
<%def name="text_types(name)">
* HTML:
* "Plain html": "${pub_url}/${name}/html/${name}.html"
* "reveal.js beige slide style": "${pub_url}/${name}/html/${name}-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "${pub_url}/${name}/html/${name}-bs.html"
* Jupyter notebook:
* "ipynb file": "${pub_url}/${name}/ipynb/${name}.ipynb"
</%def>
<%def name="slide_types(name)">
</%def>
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.
% for ch in published:
===== ${chapters[ch]} =====
${text_types(ch)}
% endfor
!split
===== Textbook =====
* PDF-file:
* "PDF file":"http://compphysics.github.io/MachineLearning/doc/LectureNotes/pdf/book.pdf"
* Jupyter notebook:
* "ipynb file": "http://compphysics.github.io/MachineLearning/doc/LectureNotes/ipynb/book.ipynb"
!split
===== Projects Fall 2021 (dates are tentative) =====
=== Project 1, Deadline October 4 (available September 10) ===
* 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"
* 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"
* Jupyter notebook:
* "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project1/ipynb/Project1.ipynb"
=== Project 2, Deadline November 13 (available October 8) ===
* 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"
* 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"
* Jupyter notebook:
* "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project2/ipynb/Project2.ipynb"
=== Project 3, Deadline December 13 (available November 12) ===
* 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"
* 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"
* Jupyter notebook:
* "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2021/Project3/ipynb/Project3.ipynb"