Deep Learning Do It Yourself!

This site collects resources to learn Deep Learning in the form of Modules available through the sidebar on the left. As a student, you can walk through the modules at your own pace and interact with others thanks to the associated digital platforms. Then we hope you'll become a contributor by adding modules to this site!

Curators

Marc Lelarge, Jill-Jênn Vie, Andrei Bursuc

For students

Pre-requisites:

• Mathematics: basics of linear algebra, probability, differential calculus and optimization

• Programming: basic proficiency Python

Annotation tool

• hypothes.is allows you to annotate this website and the web in general. You'll find some hints for the practicals here!

Social interactions

• Discord: discussion (we encourage you to hang out here during class!)

• Forum: discussion

For contributors

Join the GitHub repo dataflowr/website and make a pull request. What are pull requests?

Evaluation

Materials from this site is used for courses at ENS and X. To validate these courses, please connect to the appropriate moodle:

• ENS Moodle: (ENS and affiliated students)

• X Moodle: (X and affiliated students)

Edit this page on Last modified: April 23, 2021. Website built with Franklin.jl and the Julia programming language.