Notes Overview

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• PyTorch is a popular deep learning framework known for its flexibility and dynamic computation graphs.
• These notes will cover essential PyTorch concepts, including tensors, autograd, modules, and optimizers.
• Example codes will be provided for common tasks such as model building, training loops, and data loading.
• Guidance on integrating PyTorch with PyTorch Lightning for streamlined training and experiment management.
• Tips and best practices for debugging, performance optimization, and reproducibility.
• Useful references and resources for further learning.