dataflowr

deep learning courses

Basics of Deep Learning

Course description

This course presents practical details of deep learning architectures, in which we’ll attempt to demystify deep learning and kick-start you into using it in your own field of interest.

During this course, you will gain a better understanding of the basis of deep learning and get familiar with its applications. Indeed, we will show you how to set up, train, debug and visualize your own neural networks.

After following this course, you will be able to understand papers, blog posts and code available online, and adapt them to your own projects. This is why we do not use high-level neural networks APIs and focus on the PyTorch library.

Pre-requisites

Mathematics: basics of linear algebra, probability, differential calculus and optimization Programming: basic proficiency Python

Forum of the course

To have access to the solutions of the practicals, you need to sign in to the forum.

Schedule