Deep Learning Tutorial notes and code. See the wiki for more info.
Python Shell
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Install libgpuarray in dlt speed tests


Deep Learning Tutorials

Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. Deep Learning is about learning multiple levels of representation and abstraction that help to make sense of data such as images, sound, and text. The tutorials presented here will introduce you to some of the most important deep learning algorithms and will also show you how to run them using Theano. Theano is a python library that makes writing deep learning models easy, and gives the option of training them on a GPU.

The easiest way to follow the tutorials is to browse them online.

Main development of this project.

Project Layout


  • code - Python files corresponding to each tutorial
  • data - data and scripts to download data that is used by the tutorials
  • doc - restructured text used by Sphinx to build the tutorial website
  • html - built automatically by doc/Makefile, contains tutorial website
  • issues_closed - issue tracking
  • issues_open - issue tracking
  • misc - administrative scripts

Build instructions

To build the html version of the tutorials, install sphinx and run doc/Makefile