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What are activation functions in PyTorch and how do you apply them?
What optimizers does PyTorch provide and how do you choose between them?
What is the computation graph in PyTorch and how does the dynamic graph differ from a static graph?
What built-in layers does PyTorch's nn module provide and how do you use the most common ones?
What are learning rate schedulers in PyTorch and how do you use them?
What loss functions does PyTorch provide and when do you use each?
What are the most important tensor operations in PyTorch?
What is autograd in PyTorch and how does it compute gradients?
What is nn.Module and how do you build a custom neural network in PyTorch?
What are nn.Sequential and other container modules in PyTorch?
What are the most important loss functions in PyTorch and when do you use each?
What optimizers does PyTorch provide and how do you configure them?
What are the most common built-in layers in torch.nn and what do they do?
How do you initialise weights in a PyTorch model?
What is PyTorch and what are its key advantages over other deep learning frameworks?
What is a PyTorch tensor and how does it differ from a NumPy array?
What are tensor data types (dtypes) in PyTorch and why do they matter?
How does broadcasting work in PyTorch and what are the rules?
How do torch.no_grad() and tensor.detach() differ, and when do you use each?
What are learning rate schedulers in PyTorch and how do you use them?
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