Overview of course material: Data Analysis and Machine Learning (weekly schedule may be revised)

Morten Hjorth-Jensen [1, 2]

[1] Department of Physics and Astronomy and Facility for Rare ion Beams and National Superconducting Cyclotron Laboratory, Michigan State University, USA
[2] Department of Physics (office FV308), University of Oslo, Norway

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 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

Week 38 September 13-17: Ridge and Lasso Regression

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

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

Week 43 October 18-22: Deep learning (Convolutional Neural Networks and Recurrent Neural Networks

Week 44 October 25-29: Dimesionality Reduction, Principal Component analysis

Week 45 November 1-5: Decision Trees and Bagging

Week 46 November 8-12: Random Forests and Gradient Boosting

Week 47 November 15-19: Gradient boosting and Support Vector Machines

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

Textbook

Projects Fall 2021 (dates are tentative)

Project 1, Deadline October 4 (available September 10)

Project 2, Deadline November 13 (available October 8)

Project 3, Deadline December 13 (available November 12)