This repository gather almost all Machine Learning practical sessions I attended during my studies at the INSA of Rouen & the University of Rouen in 2013 and 2014.
For most of theses sessions, the point was to implement Machine Learning algorithms to get a sense of how they work.
Also, having been written in French schools, most of the comments are in French, although I sometimes wrote them in English. Sorry for non-French speakers. However, code and charts should be understandable.
Each practical session consist of a folder containing the sources (that you should be able to run) and a report of the results as a PDF file.
Each session is numbered x.y, where x correspond to the number of the course, and y correspond to the number of the practical session of the course. I numbered the courses approximately chronologically.
The code is either in Matlab (for the most part) or in Python (for a few ones).
For each session, the main file that should be run is usually prefixed by an underscore.
For Matlab, the following libraries might be needed:
- CVX (very often)
- SimpleMKL (very often for
monqp.m) - PROPACK (rarely)
- PRTools (very rarely)
- SOM Toolbox (very rarely)
For Python you will need the scipy environment, pickle, pykalman and yahmm.
The code is available as a Python file or a IPython Notebook.