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Courses

Du Machine Learning au Deep Learning

Course Details

Objectives : Understanding the challenges of machine learning and artificial intelligence
Know the different approaches to a machine learning problem: supervised / unsupervised / semi-supervised, regression / classification etc.
Understand the advantages and disadvantages of deep and wide neural networks
Knowing how to quantify the memory footprint and the complexity of calculating a network in the learning or evaluation phase

Duration and terms : 2 days

Notes : The teaching team is made up of teacher-researchers from the Grenoble INP - Phelma school and researchers from the Grenoble Images Parole Signal Automatique laboratory (GIPSA Lab). This training is based on the technical resources of the Grenoble INP - Phelma school.

Partnerships with national organisations : Grenoble INP - Phelma & GIPSA Lab

Dedicated web site : https://formation-continue.grenoble-inp.fr/formations-courtes/du-machine-learning-au-deep-learning?RH=1522396606568&LANGUE=0#page-presentation

Space Technologies and Scientific Disciplines