Skip to Content
Deep Learning with PyTorch
book

Deep Learning with PyTorch

by Vishnu Subramanian
February 2018
Intermediate to advanced
262 pages
6h 59m
English
Packt Publishing
Content preview from Deep Learning with PyTorch

Our first neural network

We present our first neural network, which learns how to map training examples (input array) to targets (output array). Let's assume that we work for one of the largest online companies, Wondermovies, which serves videos on demand. Our training dataset contains a feature that represents the average hours spent by users watching movies on the platform and we would like to predict how much time each user would spend on the platform in the coming week. It's just an imaginary use case, don't think too much about it. Some of the high-level activities for building such a solution are as follows:

  • Data preparation: The get_data function prepares the tensors (arrays) containing input and output data
  • Creating learnable parameters ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Deep Learning with PyTorch

Deep Learning with PyTorch

Eli Stevens, Thomas Viehmann, Luca Pietro Giovanni Antiga
Grokking Deep Learning

Grokking Deep Learning

Andrew W. Trask

Publisher Resources

ISBN: 9781788624336Supplemental Content