ECTS Maths : 3    ECTS Info : 2    Cours de Période 2   

• Teacher Stéphane Gaïffas
• Website of the course https://stephanegaiffas.github.io/deep_learning/
• Link to the course's Moodle
• Prérequis
• Modalités de validation du cours Contrôle continu
• Volume horaire du cours 2h de cours + 1h de travaux pratiques par semaine
• Durée 10 semaines

Syllabus

• Entrainement et usage des réseaux de neurones profonds

Sommaire

• Introduction to Deep Learning
• Forward and backward propagation and solvers
• Embeddings, matrix factorization, factorization machines and recommender systems
• Convolutional neural networks for image classification
• Network architectures for object detection and image segmentation
• Recurrent neural networks, Long Short-Term Memory (LSTM) units for learning based on sequences
• Learning for sequences to sequences, attention and memory
• Unsupervised deep learning and generative models

Bibliographie

• Goodfellow, I. and Bengio, Y., and Courville, A. (2016). Deep Learning. MIT Press.
• Chollet, F. and Allaire, J. J. (2018). Deep Learning with R. Manning Pub.
• Chollet, F. and Allaire, J. J. (2018). Deep Learning with Python. Manning Pub.