Course Content
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Lectures
The first set of slides is used to introduce Machine Learning, the importance of the features and how a model is learned in order to avoid some problematic situations.
Another document can also be used in order to complete what has been studied in class.
Practical Sessions
The following notebook propose to study, on simulated and real datasets, the behavior of several algorithms in Machine Learning. It is decomposed into several parts. The first ones focuses on the theoretical concept of Machine Learning before going on with the study of main algorithms with their strengths and weaknesses. It is not required to have a high level in programming to work on it since most of questions just ask you to observe and describe the results. You'll be invited to run your own algorithm at the end of the notebook with on some dedicated datasets
Team Project
Below you will find all the elements necessary to complete your project, namely the topic and the various datasets to be used.