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Explore the migration of Wolfram's Neural Network framework to a PyTorch backend and discover how eager execution unlocks powerful new capabilities in this 29-minute technical presentation. Learn how the new software architecture enables seamless integration of symbolic network graphs with imperative layer execution and native Wolfram Language functions. Understand the practical implications of combining custom Wolfram Language code with PyTorch-powered layers and pre-trained models, and see how this hybrid approach opens up new possibilities for neural network development and deployment within the Wolfram ecosystem.
