Educational repository for Washington University's T81-558 'Applications of Deep Neural Networks' course by Jeff Heaton. It is a collection of over 60 Jupyter notebooks that serve as a textbook and hands-on labs, covering PyTorch fundamentals, tabular data, computer vision (CNNs, transfer learning), time series (LSTM, transformers), generative AI (Hugging Face, LLMs, diffusion), facial processing, explainability, reinforcement learning, and more. The code is heavily pedagogical—designed for teaching, not production—with extensive markdown, inline comments, and reproducible training loops. All datasets are standard benchmarks (e.g., Auto MPG, Iris, sunspots) hosted externally or via sklearn. The repository has no CI/CD, tests, or deployment artifacts; it is purely instructional material accompanying a published arXiv textbook.