440: MuZero: Learning Without Rules

Deep Learning Illustrated is a comprehensive guide to deep learning, offering a unique visual and interactive approach. It explains deep learning techniques through straightforward analogies, vivid illustrations, and hands-on Python code in Jupyter notebooks. The book covers essential theory, including artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), and deep reinforcement learning. It also focuses on practical applications such as machine vision, natural language processing, image generation, and game-playing algorithms, using libraries like Keras, TensorFlow, and PyTorch.

This book provides an accessible introduction to deep reinforcement learning, covering both the theoretical foundations and practical implementations of popular algorithms like REINFORCE, SARSA, DQN, and PPO. It includes code examples using PyTorch and the SLM Lab library, making it ideal for computer science students and software engineers familiar with Python and basic machine learning concepts.