Crash course in Deep Learning and PyTorch
09:00 - 16:30, 28 January

full day
Beginner level

@ Room 4ACB

Details

Basics in deep learning with examples in pytorch.

Outcome

Understanding of convolutional networks, standard optimization methods, pytorch tensors, autograd, and deep-learning specific modules.

Prerequisites

  • knowledge of python programming
  • basics of linear algebra and statistics

Organisers

Francois Fleuret

Head of the Machine Learning group, Idiap Research Institute

Website