Introduction to Torch

author: Alex Wiltschko, Twitter, Inc.
published: Aug. 23, 2016,   recorded: August 2016,   views: 459
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Torch is an open platform for scientific computing in the Lua language, with a focus on machine learning, in particular deep learning. Torch is distinguished from other array libraries by having first-class support for GPU computation, and a clear, interactive and imperative style. Further, through the "NN" library, Torch has broad support for building and training neural networks by composing primitive blocks or layers together in compute graphs. Torch, although benefitting from extensive industry support, is a community owned and community developed ecosystem.

All neural net libraries, including Torch NN, rely on automatic differentiation (AD) to manage the computation of gradients of complex compositions of functions. I will also present some general background on automatic differentiation (AD), which is the fundamental abstraction of gradient-based optimization, and demonstrate Twitter's flexible implementation of AD in the library torch-autograd.

See Also:

Download slides icon Download slides: deeplearning2016_wiltschko_torch_01.pdf (7.4┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: