Intro to Deep Learning with PyTorch

About this resource

The Intro to Deep Learning with PyTorch workshop from Udacity will walk you through introductory deep learning concepts as well as how to build a neural networks in PyTorch. PyTorch is one of the most popular deep learning frameworks. Known for its speed and more “Pythonic” feel, it is frequently the go-to choice for most researchers. The biggest downside of PyTorch, compared to a high-level framework like Keras, is that it is quite verbose. That is, you’ll need to write a couple hundred lines of code to train and evaluate your neural network. Keras is a great alternative for those who are just getting started with neural networks or those that don’t need to train many models, as you can train/evaluate in just a dozen or so lines of code.

Prerequisites

Learners are expected to have the following knowledge:

• Basic Python programming skills and familiarity with the Pandas package. If you need a refresher, these Introductory Python lesson materials are available for independent study.

Estimated time to complete

TBD: Use the Improve this page functionality to add your own estimate!

Questions?

If you any lingering questions about this resource, please feel free to post to the Nexus Q&A on GitHub. We will improve materials on this website as additional questions come in.

See also

• Workshop: Intro to Deep Learning with Keras: Explore Keras as an alternative deep learning framework
• Book: Understanding Deep Learning - Simon J.D. Prince: This free textbook is a good modern overview of deep learning, and provides colab notebooks to explore deep learning concepts and implementations. The book uses PyTorch as its framework of choice. You may find additional details in this book that the workshop only briefly touches on.