Learn all the basics you need to get started with this deep learning framework! In this part we improve the code from the last part and will learn how a complete training pipeline is implemented in PyTorch. We replace the manually computed loss and weight updates with a loss and an optimizer from the PyTorch framework, which can do the optimization for us. We will then see how a PyTorch model is implemented and used for the forward pass.
Official website:
https://pytorch.org/
Code for this tutorial series:
https://github.com/python-engineer/pytorchTutorial
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