Françoise Bouvet, "Initiation au Machine Learning"

Europe/Paris
200/1-101 - Salle 101 (IJCLab)

200/1-101 - Salle 101

IJCLab

50
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Description

Summary

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

  • Good practice of Python.
  • Knowledge of main Python libraries : numpy, matplotlib, pandas.

Registration

While it is now possible for all lab members to register via Indico, note that this course was initially proposed as a doctoral school training and PhD students registering via ADUM will accordingly get priority for the initial run. If there is too much demand, the course will be run again later in the year.

Participants
6
L'ordre du jour de cette réunion est vide