jcjohnson/pytorch-examples
Self-contained examples teaching PyTorch fundamentals including tensors, autograd, neural network modules, and gradient descent training.
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This repository walks through PyTorch’s core features through a hands-on running example: training a fully-connected ReLU network with a single hidden layer using gradient descent to fit random data. It covers tensors, automatic differentiation, nn modules, optimizers, and custom autograd functions. It also includes comparable numpy and TensorFlow implementations for context.
Frequently asked
- What is jcjohnson/pytorch-examples?
- Self-contained examples teaching PyTorch fundamentals including tensors, autograd, neural network modules, and gradient descent training.
- Is pytorch-examples open source?
- Yes — jcjohnson/pytorch-examples is open source, released under the MIT license.
- What language is pytorch-examples written in?
- jcjohnson/pytorch-examples is primarily written in Python.
- How popular is pytorch-examples?
- jcjohnson/pytorch-examples has 4.9k stars on GitHub.
- Where can I find pytorch-examples?
- jcjohnson/pytorch-examples is on GitHub at https://github.com/jcjohnson/pytorch-examples.