NOTE: THIS TUTORIAL HAS BEEN MOVED TO THIS LOCATION, and will be updated there regularly.
These tutorials were designed for the IPAM Summer School on Deep Learning: more info here..
This directory contains four tutorials, which intend to teach how to train deep-learning models using supervised and unsupervised techniques, using Torch7.
The Torch tutorials are less interactive than the IPython ones. Rather, they give you complete end-to-end programs, which you can use as a solid starting point to develop your own programs/scripts.
These tutorials should be read/done in order.
This text can be browsed either from the html files, or directly on GitHub, by navigating through the directory structure.
If you're reading this on GitHub, you won't see the Math properly rendered, please read the tutorials here.
HTML Links (if you're browsing an HTML version of this help, i.e. not GitHub):
- Day 1: Setup / Basics / Getting Started
- Day 2: Supervised Learning
- Day 3: Unsupervised Learning
- Day 4: Graphical Models
- Days 5+: Going Further
GitHub Links: