The objective of this workshop is to present the current available software and hardware solutions for deep machine learning. We will focus on the two main industrial frameworks for the task: Facebook's Torch and Google's TensorFlow, and will discuss the general principles of deep learning, best practices, "under the hood" mechanisms, and the existing hardware solutions to deal with the specific computational requirements of these methods.

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Deep Supervised Learning of Representations
Yoshua Bengio, University of Montreal, Canada
4 juil. 2016 · 2:01 après-midi
1 626 views
Hardware & software update from NVIDIA, Enabling Deep Learning
Alison B Lowndes, NVIDIA
4 juil. 2016 · 3:20 après-midi
306 views
Day 1 - Questions and Answers
Panel
4 juil. 2016 · 4:16 après-midi
253 views
Torch 1
Soumith Chintala, Facebook
5 juil. 2016 · 10:02 matin
639 views
Torch 2
Soumith Chintala, Facebook
5 juil. 2016 · 11:21 matin
232 views
Deep Generative Models
Yoshua Bengio, University of Montreal, Canada
5 juil. 2016 · 1:59 après-midi
972 views
Torch 3
Soumith Chintala, Facebook
5 juil. 2016 · 3:28 après-midi
205 views
Day 2 - Questions and Answers
Panel
5 juil. 2016 · 4:21 après-midi
113 views
TensorFlow 1
Mihaela Rosca, Google
6 juil. 2016 · 10 matin
1 251 views
TensorFlow 2
Mihaela Rosca, Google
6 juil. 2016 · 11:19 matin
542 views
AMD's Open Compute and Open Source cross platform solutions for Machine Learning
Mauricio Breternitz, AMD
6 juil. 2016 · 1:59 après-midi
161 views
TensorFlow 3 and Day 3 Questions and Answers session
Mihaela Rosca, Google
6 juil. 2016 · 3:21 après-midi
469 views