dsgiitr/d2l-pytorch

This resource provides practical examples and explanations for fundamental and advanced deep learning concepts, translating the content of the 'Dive Into Deep Learning' book from MXNet to PyTorch. It helps deep learning practitioners understand and implement various neural network architectures and techniques, offering code snippets and explanations for tasks like image classification and regression. The primary users are machine learning engineers, data scientists, and researchers looking to apply deep learning models.

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