The core mechanics of Deep Learning, and how to think the PyTorch way. This guide provides a whirlwind tour of PyTorch’s methodologies and design principles, covering tensors, automatic differentiation, and training custom neural networks.
This tutorial introduces the essential topics of the PyTorch deep learning library in about one hour. It covers tensors, training neural networks, and training models on multiple GPUs.
A deep dive into the theory and applications of diffusion models, focusing on image generation and other tasks, with examples and PyTorch code.
