Learn and practice PyTorch, a framework for developing deep learning models.

Become a Deep Learning Professional

In this module, we’ll be introduced to the fundamentals of PyTorch: autograd, model classes, datasets, data loaders, and more. We’ll develop models and understand them step-by-step. We'll understand the reasoning behind the code and how to avoid some common pitfalls and errors along the way.
By the time we finish this module, we’ll have a thorough understanding of the concepts and tools necessary to start developing and training our own models using PyTorch.

Deep Learning with PyTorch

## Solution

The following is the Jupyter notebook, which contains the answers to your third challenge. Click on it to launch the application.

# Solution

The following is the Jupyter notebook, which contains the answers to your third challenge. Click on it to launch the application.

This review explains the solution for the "Rethinking the Training Loop" challenge.

Introduction

Visualizing Gradient Descent

A Simple Regression Problem

Rethinking the Training Loop

Going Classy

A Simple Classification Problem

Appendix

Conclusion

Solution Review - Rethinking the Training Loop

Solution