PyTorch Tutorial 13 – Feed-Forward Neural Network

New Tutorial series about Deep Learning with PyTorch!
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In this part we will implement our first multilayer neural network that can do digit classification based on the famous MNIST dataset.

We put all the things from the last tutorials together:

– Use the DataLoader to load our dataset and apply a transform to the dataset
– Implement a feed-forward neural net with input layer, hidden layer, and output layer
– Apply activation functions.
– Set up loss and optimizer
– Training loop that can use batch training.
– Evaluate our model and calculate the accuracy.
– Additionally, we will make sure that our whole code can also run on the gpu if we have gpu support.

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Part 13: Feed-Forward Neural Network

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Official website:
https://pytorch.org/

Part 01:

Code for this tutorial series:
https://github.com/python-engineer/pytorchTutorial

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