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Learn how to transition from PyTorch 2's stateful operations to JAX's functional programming approach in this 21-minute tutorial video. Compare implementations of neural network model definition and training using torch.nn.Module with equivalent JAX code for regression via gradient descent. Explore practical examples demonstrating how to convert stateful operations to stateless ones in JAX, with a focus on handling model parameters as state. Access complementary resources including official JAX documentation and hands-on practice through a free Google Colab notebook to reinforce learning concepts in parallel computing and AI development.
