Description
Product Description
Deep learning is one of today’s hottest fields. This approach to machine learning is achieving breakthrough results in some of today’s highest profile applications, in organizations ranging from Google to Tesla, Facebook to Apple. Thousands of technical professionals and students want to start leveraging its power, but previous books on deep learning have often been non-intuitive, inaccessible, and dry. In Deep Learning Illustrated, three world-class instructors and practitioners present a uniquely visual, intuitive, and accessible high-level introduction to the techniques and applications of deep learning. Packed with vibrant, full-color illustrations, it abstracts away much of the complexity of building deep learning models, making the field more fun to learn, and accessible to a far wider audience.
Part I’s high-level overview explains what Deep Learning is, why it has become so ubiquitous, and how it relates to concepts and terminology such as Artificial Intelligence, Machine Learning, Artificial Neural Networks, and Reinforcement Learning. These opening chapters are replete with vivid illustrations, easy-to-grasp analogies, and character-focused narratives.
Building on this foundation, the authors then offer a practical reference and tutorial for applying a wide spectrum of proven deep learning techniques. Essential theory is covered with as little mathematics as possible, and illuminated with hands-on Python code. Theory is supported with practical “run-throughs” available in accompanying Jupyter notebooks, delivering a pragmatic understanding of all major deep learning approaches and their applications: machine vision, natural language processing, image generation, and videogaming.
To help readers accomplish more in less time, the authors feature several of today’s most widely-used and innovative deep learning libraries, including TensorFlow and its high-level API, Keras; PyTorch, and the recently-released high-level Coach, a TensorFlow API that abstracts away the complexity typically associated with building Deep Reinforcement Learning algorithms.
Review
“Over the next few decades, artificial intelligence is poised to dramatically change almost every aspect of our lives, in large part due to today’s breakthroughs in deep learning. The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come.”
―Tim Urban, writer and illustrator of Wait But Why
“This book is an approachable, practical, and broad introduction to deep learning, and the most beautifully illustrated machine learning book on the market.”
―Dr. Michael Osborne, Dyson Associate Professor in Machine Learning, University of Oxford
“This book should be the first stop for deep learning beginners, as it contains lots of concrete, easy-to-follow examples with corresponding tutorial videos and code notebooks. Strongly recommended.”
―Dr. Chong Li, cofounder, Nakamoto & Turing Labs; adjunct professor, Columbia University
“It’s hard to imagine developing new products today without thinking about enriching them with capabilities using machine learning. Deep learning in particular has many practical applications, and this book’s intelligible clear and visual approach is helpful to anyone who would like to understand what deep learning is and how it could impact your business and life for years to come.”
―Helen Altshuler, engineering leader, Google
“This book leverages beautiful illustrations and amusing analogies to make the theory behind deep learning uniquely accessible. Its straightforward example code and best-practice tips empower readers to immediately apply the transformative technique to their particular niche of interest.”
–Dr. Rasmus Rothe, founder, Merantix
“This is an invaluable resource for anyone looking to understand what deep learning is and why it powers almost every automated application today,