The math inside PyTorch's engine — how linear algebra, calculus & optimization drive torch.autograd, torch.nn, and torch.optim. GHC 2025 talk materials.
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Updated
Nov 27, 2025
The math inside PyTorch's engine — how linear algebra, calculus & optimization drive torch.autograd, torch.nn, and torch.optim. GHC 2025 talk materials.
Zero to Mastery ML/DL/DS courses by Daniel Bourke
A comprehensive repository covering the fundamentals to advanced concepts of building, training, and optimizing neural networks using PyTorch, including practical implementations for computer vision, NLP, and modern AI techniques.
This project implements the classical LeNet-5 CNN for MNIST digit classification using PyTorch. It covers a complete pipeline from data preprocessing to deployment. The model achieves ~98.8% test accuracy, showing the strong effectiveness of early CNN architectures for image classification.
This is a repository that records the experiment and training process from deep learning model design to optimization.
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