This repository is a comprehensive resource for learning PyTorch, designed to guide you through deep learning concepts from A to Z. It contains two main components: detailed examples from the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann, and a curated series of notebooks covering PyTorch fundamentals, workflows, classification, custom datasets, transfer learning, model deployment, and more. Each notebook provides step-by-step explanations, practical recommendations, and hands-on examples to help users master PyTorch for various machine learning tasks. Explore and utilize the materials to enhance your understanding of PyTorch and deep learning!