Recap
Explore the core concepts covered in implementing a linear regression model with PyTorch. Understand tensors, autograd for automatic differentiation, optimizer usage, loss functions, and the PyTorch Module class. This lesson helps consolidate your knowledge of building and training models effectively, preparing you for more advanced topics.
We'll cover the following...
We'll cover the following...
General overview
First of all, congratulations are in order! You have successfully implemented a fully functioning model and training loop in PyTorch!
We have covered a lot of ground in this third chapter:
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Implementing a linear regression in Numpy using gradient descent.
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Creating tensors in PyTorch, sending them to a device, and making parameters out of them.
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Understanding PyTorch’s main feature, ...