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Foundations of Deep Reinforcement Learning
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games—such as Go, Atari games, and DotA 2—to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software lib...
Deep Learning Illustrated
"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, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable a...
Machine Learning with Python for Everyone
The Complete Beginner’s Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you’re an absolute beginner. If you can write some Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning. Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you t...
Supercharged Python
“Brian Overland makes programming simple. . . . To my amazement, his books explain complicated code clearly enough for anyone to understand.” —Art Sedighi, PhD Tapping into the full power of Python doesn’t have to be difficult. Supercharged Python is written for people who’ve learned the fundamentals of the language but want to take their skills to the next level. After a quick review of Python, the book covers: advanced list and string techniques; all the ways to handle text and binary files; financial applications; advanced techniques for writing classes; generators and decorators; and how to master packages such as Numpy (Numeric Python) to supercharge your applications! Use pro...
Decision Making Under Uncertainty
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorit...
Reinforcement Learning, second edition
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the fir...
Reinforcement Learning
Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcementand enable a machine to learn by itself. Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learnnumerous algorithms, and benefit from dedicated chapters on deploying RL solutions to productio...
Fear of Writing
The maestro of political plays is back and his latest offering in a decade, Fear of Writing, is a groundbreaking commentary with its finger on the political pulse of Singapore today. In Fear of Writing, a playwright struggles with writer’s block, a director and producer bemoan their failure to get a government license to stage their play, and a father writes to his daughter overseas. Seemingly disparate elements are woven together, while the line between art, performance and reality begin to blur dramatically as the play reaches its chilling conclusion. Fear of Writing is a play that will haunt you while compelling you to decide where you stand on the issues of control and censorship. Written by Tan Tarn How, Fear of Writing was first staged by Theatreworks in 2011 to critical acclaim.
The Cartoon Introduction to Economics, Volume I: Microeconomics
The award-winning illustrator Grady Klein has paired up with the world's only stand-up economist, Yoram Bauman, PhD, to take the dismal out of the dismal science. From the optimizing individual to game theory to price theory, The Cartoon Introduction to Economics is the most digestible, explicable, and humorous 200-page introduction to microeconomics you'll ever read. Bauman has put the "comedy" into "economy" at comedy clubs and universities around the country and around the world (his "Principles of Economics, Translated" is a YouTube cult classic). As an educator at both the university and high school levels, he has learned how to make economics relevant to today's world and today's stude...
Deep Reinforcement Learning Hands-On
Revised and expanded to include multi-agent methods, discrete optimization, RL in robotics, advanced exploration techniques, and more Key Features Second edition of the bestselling introduction to deep reinforcement learning, expanded with six new chapters Learn advanced exploration techniques including noisy networks, pseudo-count, and network distillation methods Apply RL methods to cheap hardware robotics platforms Book DescriptionDeep Reinforcement Learning Hands-On, Second Edition is an updated and expanded version of the bestselling guide to the very latest reinforcement learning (RL) tools and techniques. It provides you with an introduction to the fundamentals of RL, along with the h...
