Program requirementsprojet
TeacherIlaria Giulini
Weekly hours 3 h CM
Years M2 Mathématiques et Informatique pour la Science des Données (DM) M2 ISIFAR M2 Mathématiques et Informatique appliquées à la Science des données M2 Logos

Syllabus

Entrainement et usage des réseaux de neurones profonds

Contents

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

Bibliography

  • 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.