Implementing and Training a Neural Network with PyTorch

Build and train a feed-forward neural network using PyTorch in this 37-minute tutorial. Develop a classifier to identify digits in the MNIST dataset while learning data management techniques with PyTorch datasets and data loaders. Follow a step-by-step implementation process, starting with PyTorch installation and dataset download. Progress through implementing a data loader, designing a feed-forward network, and creating a training loop. Conclude by training and storing the model, gaining practical experience in neural network development with PyTorch.

Intro
Installing PyTorch with pip
Step-by-step implementation overview
Download datasets
Implementing a data loader
Implementing a feed forward network
Implementing the training loop
Training and storing our model
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