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1
Intro
2
Installing PyTorch with pip
3
Step-by-step implementation overview
4
Download datasets
5
Implementing a data loader
6
Implementing a feed forward network
7
Implementing the training loop
8
Training and storing our model
9
Coming up next + outro
Description:
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.

Implementing and Training a Neural Network with PyTorch

Valerio Velardo - The Sound of AI
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