Deep Learning with PyTorch

This repo contains notebooks and related code for Udacity's Deep Learning with PyTorch lesson. This lesson appears in our AI Programming with Python Nanodegree program.

• Part 1: Introduction to PyTorch and using tensors
• Part 2: Building fully-connected neural networks with PyTorch
• Part 3: How to train a fully-connected network with backpropagation on MNIST
• Part 4: Exercise - train a neural network on Fashion-MNIST
• Part 5: Using a trained network for making predictions and validating networks
• Part 6: How to save and load trained models
• Part 7: Load image data with torchvision, also data augmentation
• Part 8: Use transfer learning to train a state-of-the-art image classifier for dogs and cats

  Archival Note

  This repository is deprecated; therefore, we are going to archive it. However, learners will be able to fork it to their personal Github account but cannot submit PRs to this repository. If you have any issues or suggestions to make, feel free to:

• Utilize the https://knowledge.udacity.com/ forum to seek help on content-specific issues.
• Submit a support ticket along with the link to your forked repository if (learners are) blocked for other reasons. Here are the links for the retail consumers and enterprise learners.