Orateur
Francoise BOUVET
(IJCLab - CNRS - UPsay)
Description
We will describe the main concepts of Machine Learning (ML) and give some clues to address a problem of ML. In particular, we will talk about :
- the concepts of AI/Machine Learning/Deep Learning,
- supervised/unsupervised learning,
- the preprocessing of the data,
- the general principle of the algorithm,
- the main pitfalls,
- the evaluation of the training and the outcomes.
Some exercises will be provided to understand the basic concepts of standard ML methods.
Prerequisites: practice of Python and main libraries (numpy, pandas, matplotlib).
