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, the Paythonic way of PyTorch, and similarities with numpy.
-
Part 2: Different ways to build fully-connected deep neural networks with PyTorch, and their forward behavior.
-
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