Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.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 when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    In this indispensable volume, a primer for the information age, Hans Christian von Baeyer presents a clear description of what information is, how concepts of its measurement, meaning, and transmission evolved, and what its ever-expanding presence portends for the future. Information is poised to replace matter as the primary stuff of the universe, von Baeyer suggests; it will provide a new basic framework for describing and predicting reality in the twenty-first century. Despite its revolutionary premise, von Baeyer's book is written simply in a straightforward fashion, offering a wonderfully accessible introduction to classical and quantum information. Enlivened with anecdotes from the lives of philosophers, mathematicians, and scientists who have contributed significantly to the field, Information conducts readers from questions of subjectivity inherent in classical information to the blurring of distinctions between computers and what they measure or store in our quantum age. A great advance in our efforts to define and describe the nature of information, the book also marks an important step forward in our ability to exploit information--and, ultimately, to transform the nature of our relationship with the physical universe. (20040301)

    Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.

    The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts which are set in abstract settings.

    A software diskette provides an easy-to-use tool for students to derive probabilities for binomial.

    This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    Maths is about patterns, and our universe is extraordinarily patterned. With enthusiasm and wonder, Eddie is here to help us discover these patterns.With engaging clarity and entertaining anecdotes, Eddie demonstrates the intricacy of maths in all the things we love - from music in our iPods to our credit cards. Filled with humour and heart, this book will fascinate, entertain and illuminate the maths that surrounds us.

    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

    The Asylum is a stunning exposé by a seasoned Wall Street journalist that once and for all reveals the truth behind America’s oil addiction in all its unscripted and dysfunctional glory.In the tradition of Too Big to Fail and Liar’s Poker, author Leah McGrath Goodman tells the amazing-but-true story of a band of struggling, hardscrabble traders who, after enduring decades of scorn from New York’s stuffy financial establishment, overcame more than a century of failure, infighting, and brinksmanship to build the world’s reigning oil empire—entirely by accident.

    Social Network Analysis: Methods and Applications reviews and discusses methods for the analysis of social networks with a focus on applications of these methods to many substantive examples. As the first book to provide a comprehensive coverage of the methodology and applications of the field, this study is both a reference book and a textbook.

    Weygandt, Paul D. Kimmel, and Donald E. Kieso, which incorporates International Financial Reporting Standards (IFRS) into the existing textbook framework. On almost every page, the book addresses every accounting topic from the perspective of IFRS while still highlighting key differences between IFRS and US GAAP. Following the reputation for accuracy, comprehensiveness, and currency, the authors have painstakingly created a book dedicated to assisting students learning accounting topics under the rules of IFRS.

    The metric gives unparalleled insight into which teams and players are performing at the highest level.Professional gamblers have used Expected Goals to make millions through football betting. Club scouts have used Expected Goals to identify hidden gems in the transfer market. And the media have recently started using Expected Goals to offer more profound insight in their broadcasts.Despite this, most ordinary fans still don’t understand what the Expected Goals method is – or appreciate the significant impact that it is set to have on the sport in coming years.Expected Goals (otherwise known as xG) was originally conjured up by a small corner of the online football analytics community. It didn’t take long for professional gamblers to begin using xG to predict match outcomes. These bettors utilised the Expected Goals method to turn over hundreds of millions of pounds from the bookmakers.Before long, football clubs had caught on to the ground-breaking insight given by xG. Brentford FC were leaders in this field, managing to assemble a Play-Off-reaching squad on a shoe-string budget. In the last five years, the small West London side have turned over more than £100m in transfer profit from their use of the Expected Goals method in player recruitment.More recently, the Expected Goals method has been adopted by the media as a form of insight. Fans are finally catching on to the pioneering means of football analysis. Soon enough, anyone who doesn’t understand the Expected Goals philosophy will be left behind.“This book will make you watch football differently” – Tobias Pedersen“Possibly the most ground-breaking football book ever written” – Football Impact“A brilliant account of the history and future of Expected Goals” – StatShot

    All that jargon, all those calculations – it’s a hard game to break into and even harder to get right from the start. On the other hand, learning the ropes opens the door to an exciting new way to calculate risk, find the right investments and ultimately make your bank balance happy.This book is here to teach you how to understand the options market from scratch. By the time you finish reading, you’ll know exactly how to navigate your choices – and how to make them with wisdom. Let's Get Started With Option Trading! Options trading is all about understanding what lies beneath the market and this guide will walk you through that exciting process.Give it ONE WEEK and you'll TRIPLE your chances of making a profit on the options market. Give it a month and you'll see you're not just confident enough to make investments at will, you’re doing so in the right way to make a tidy deposit into your trading account. In this book, we’ll cover: ·         The types of trade and how each one can bring you a profit.·         Strategies to make the very best use of your investment capital.·         How to see patterns in the market, how to spot great investments – and how to make money.·         And much, MUCH more. If You Don't Read This Guide, You Risk LOSING YOUR LIFE SAVINGS on the Options Market These methods has been proven to work – a hundred times over. This book will show you that understanding the basic principles of the options market is not nearly so unfathomable as it appeared from a distance. All it takes is a few easy steps and you’ll start to feel a difference within a few short days – and all for less than the cost of a pocket calculator. See the Difference in Less Than a Week... or Your Money Back! If you follow the chapters in this guide and you find they don't work (not gonna happen) or you feel like they’re not for you, simply click one button within 7 days and Amazon will return 100% of your money. That’s how confident I am the answer to your problem is found inside – You will learn how to successfully trade options.Just scroll up now and click the BUY NOW button to start making a profit, today!

    The book is non-theoretical, explaining concepts intuitively and teaching problem solving through worked examples and step-by-step instructions. This edition places more emphasis on conceptual understanding and understanding results. This edition also features increased emphasis on Excel, MINITAB, and the TI-83 Plus and TI 84-Plus graphing calculators, computing technologies commonly used in such courses.