Deep Learning DIY
source link: https://dataflowr.github.io/website/
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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
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)
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