The Fundamentals of Modern Deep Learning with PyTorch

Explore the fundamentals of modern deep learning with PyTorch in this comprehensive 3-hour tutorial aimed at Python programmers new to PyTorch and deep learning. Learn how to train neural networks for image and text classification while discussing the strengths and weaknesses of deep learning compared to traditional machine learning. Dive deep into the PyTorch library, understanding its structure as a tensor library, automatic differentiation library, and framework for implementing deep neural networks. Discover additional open source libraries like PyTorch Lightning to familiarize yourself with the modern deep learning stack, enabling mixed-precision techniques and multi-GPU training. Run model code on a laptop computer or take advantage of free GPU options via Google Colab and Lightning for enhanced training capabilities. Access tutorial materials and additional information on GitHub, where a Discussion Forum is available for pre-event questions. Gain a solid foundation in PyTorch and modern deep learning techniques, with potential exposure to new concepts even for experienced practitioners.

Tutorials - Sebastian Raschka: The Fundamentals of Modern Deep Learning with PyTorch