Details

Faculty	Faculty of Science and Medicine
Domain	Mathematics
Code	UE-SMA.03413
Languages	French , English
Type of lesson	Lecture
Level	Bachelor
Semester	AS-2021

Schedules and rooms

Summary schedule	Monday 13:15 - 15:00, Hebdomadaire (Autumn semester)
Hours per week	2

Teaching

Responsibles	Mazza Christian
Teachers	Mazza Christian
Description	This course aims at presenting and studying mathematically models from statistical learning theory, by focusing on deep learning algorithms in multi-layer neural networks. Applications to artificial intelligence will be provided. We will also present and study the basic probabilistic and statistical models of machine learning by making links with neural nets. A special emphasis will be given to deep learning processes for Boltzmann machines using methods from probability theory, statistics and statistical mechanics.
Training objectives	Topics focus on but are not limited to: Biological neural networks, mathematical models of neural nets, learning algorithms (Hebb rule) for Hop eld neural nets and Boltzmann machines, machine learning and multivariate statistics (discriminant analysis, regression), general statistical learning theory (deterministic and stochastic models, Vapnik-Cervonenkis theory), learning processes in associative memories, perceptron and multi-layer neural nets, stochastic processes for deep learning in Boltzmann machines, thermodynamic extension (statistical mechanics of learning processes)
Comments	compte pour Mathématiques appliquées
Softskills	No
Off field	No
BeNeFri	Yes
Mobility	Yes
UniPop	No

Oral exam - AS-2021, Session d'hiver 2022

Assessments methods

By rating

Oral exam - SS-2022, Session d'été 2022

Assessments methods

By rating

Oral exam - SS-2022, Autumn Session 2022

Assessments methods

By rating