Descriptif

Teachers: Geoffroy Peeters, Alasdair Newson (Telecom Paris, IP-Paris)

Abstract: Deep Learning (machine learning based on deep artificial neural networks) has become extremely popular over the last years due to the very good results it allows for tasks such as regression, classification or generation.

The objective of this course is to provide a theoretical understanding
and a practical usage of the three main types of networks (Multi-Layer-
Perceptron, Recurrent-Neural-Network and Convolutional Neural Network).

The content of this course ranges from the perceptron to the generation of adversarial images.

Each theoretical lecture is followed by a practical lab on the corresponding content where student learn to implement these networks using the currently three popular frameworks: pytorch, tensorflow and keras.

Format : 6 sessions of 4 hours + Exam

Grading : 30% labs/project + 70% written exam