This up-to-date guide to deep learning is intended for students in computer science, electrical engineering, data science, statistics, and OR as well as researchers in academia and industry. State-of-the-art topics include transformers, GNNs, VAEs, and deep RL. Complementary code and hundreds of exercises with solutions are provided on the website.
