Learning PyTorch with Examples
This tutorial introduces the fundamental concepts of PyTorch through self-contained examples. At its core, PyTorch provides two main features: An n-dimensional Tensor, similar to numpy but can run on GPUs Automatic differentiation for building and training neural networks We will use a problem of fitting y=sin(x) with a third order polynomial as our running example. The network will have four parameters, and will be trained with gradient descent to fit random data by minimizing the Euclidean distance between the network output and the true output.
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