Deep Learning Illustrated

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 organisations 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-colour 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.

Preview sample pages from Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence >

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.

“"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, from chatbots and voice recognition tools to self-driving cars. The illustrations and biological explanations help bring to life a complex topic and make it easier to grasp fundamental concepts." -Joshua March, CEO and cofounder, Conversocial; author of Message Me "Deep learning is regularly redefining the state of the art across machine vision, natural language, and sequential decision-making tasks. If you too would like to pass data through deep neural networks in order to build high-performance models, then this book-with its innovative, highly visual approach-is the ideal place to begin." -Dr. Alex Flint, roboticist and entrepreneur”

“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, from chatbots and voice recognition tools to self-driving cars. The illustrations and biological explanations help bring to life a complex topic and make it easier to grasp fundamental concepts.”
–Joshua March, CEO and cofounder, Conversocial; author of Message Me

“Deep learning is regularly redefining the state of the art across machine vision, natural language, and sequential decision-making tasks. If you too would like to pass data through deep neural networks in order to build high-performance models, then this book–with its innovative, highly visual approach–is the ideal place to begin.”
–Dr. Alex Flint, roboticist and entrepreneur

Jon Krohn is the chief data scientist at untapt, a machine learning startup in New York. He leads a flourishing Deep Learning Study Group, presents the acclaimed Deep Learning with TensorFlow LiveLessons in Safari, and teaches his Deep Learning curriculum at the NYC Data Science Academy. Jon holds a doctorate in neuroscience from Oxford University and has been publishing on machine learning in leading academic journals since 2010.

Grant Beyleveld is a doctoral candidate at the Icahn School of Medicine at New York's Mount Sinai hospital, researching the relationship between viruses and their hosts. A founding member of the Deep Learning Study Group, he holds a masters in molecular medicine and medical biochemistry from the University of Witwatersrand.

Aglaé Bassens is a Belgian artist based in Brooklyn. She studied fine arts at The Ruskin School of Drawing and Fine Art, Oxford University, and University College London's Slade School of Fine Arts. Along with her work as an illustrator, her practice includes still life painting and murals.

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 is 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. Ideal for software developers, data scientists, and analysts at all levels of experience Teaches through simple visuals, accessible Python code examples, character-driven narratives, and intuitive analogies Covers today's leading applications, including machine vision, natural language processing, image generation, and videogames Introduces four powerful Deep Learning libraries: TensorFlow, Keras, PyTorch, and Coach Carefully designed to minimize mathematical formulae and avoid unnecessary complexity The first full-color, illustrated, hands-on guide to the fundamentals of modern, deep-learning AI: simply the most intuitive, practical way to get started Ideal for software developers, data scientists, and analysts at all levels of experience Teaches through simple visuals, accessible Python code examples, character-driven narratives, and intuitive analogies Covers today's leading applications, including machine vision, natural language processing, image generation, and videogames Introduces four powerful Deep Learning libraries: TensorFlow, Keras, PyTorch, and Coach Carefully designed to minimize mathematical formulae and avoid unnecessary complexity

"This book is a stunning achievement, written with precision and depth of understanding. It entertains you and gives you lots of interesting information at the same time. I could never imagine understanding and gaining scientific knowledge, namely 'Deep Learning' can be this much fun! Reading the book is a pleasure and I highly recommend it."--maryamkhakpour, O'Reilly Online Learning (Safari) Reviewer "This title is a great resource for those looking to understand deep learning. The illustrations are helpful and aid in cementing a richer understanding of the content, and the background context surrounding biological motivations for the tools and techniques enables a greater appreciation of the field. I enthusiastically recommend this book to any and all who are interested in the topic of deep learning." -vincepetaccio, O'Reilly Online Learning (Safari) Reviewer Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely visual, intuitive, and accessible, and yet offers a comprehensive introduction to the discipline's techniques and applications. Packed with full-color applications and easy-to-follow code, it sweeps away much of the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn-with crucial material from Grant Beyleveld and beautiful illustrations by Agla

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