What if everything in life could be reduced to a simple formula? What if numbers were able to tell us which partners we were best matched with – not just in terms of attractiveness, but for a long-term committed marriage? Or if they could say which films would be the biggest hits at the box office, and what changes could be made to those films to make them even more successful? Or even who out of us is likely to commit certain crimes, and when? This may sound like the world of science-fiction, but in fact it is just the tip of the iceberg in a world that is increasingly ruled by complex algorithms and neural networks.In The Formula, Luke Dormehl takes you inside the world of numbers, asking how we came to believe in the all-conquering power of algorithms; introducing the mathematicians, artificial intelligence experts and Silicon Valley entrepreneurs who are shaping this brave new world, and ultimately asking how we survive in an era where numbers can sometimes seem to create as many problems as they solve.

    Indeed, no other legislature in the world approaches its power. Yet most Americans have only a murky idea of how it works. In The U.S. Congress, Donald A. Ritchie, a congressional historian for more than thirty years, takes readers on a fascinating, behind-the-scenes tour of Capitol Hill--pointing out the key players, explaining their behavior, and translating parliamentary language into plain English. No mere civics lesson, this eye-opening book provides an insiders perspective on Congress, matched with a professional historians analytical insight. After a swift survey of the creation of Congress by the constitutional convention, he begins to unscrew the nuts and pull out the bolts. What is it like to campaign for congress? To attract large donors? To enter either house with no seniority? He answers these questions and more, explaining committee assignments (and committee work), the role of staffers and lobbyists, floor proceedings, parliamentary rules, and coalition building. Ritchie explores the great effort put into constituent service--as representatives and senators respond to requests from groups and individuals--as well as media relations and news coverage. He also explores how the grand concepts we all know from civics class--checks and balances, advise and consent, congressional oversight--work in practice, in an age of strong presidents and a muscular Senate minority (no matter which party is in that position). In this sparkling addition to Oxfords Very Short Introduction series, Donald Ritchie moves beyond the cynicism and the platitudes to provide a gem of a portrait of how Congress really works.

    Even as we approach its fiftieth anniversary, the movement remains so contentious that the Chinese Communist Party still forbids fully open investigation of its origins, development, and conclusion. Drawing upon a vital trove of scholarship, memoirs, and popular culture, this Very Short Introduction illuminates this complex, often obscure, and still controversial movement. Moving beyond the figure of Mao Zedong, Richard Curt Kraus links Beijing's elite politics to broader aspects of society and culture, highlighting many changes in daily life, employment, and the economy. Kraus also situates this very nationalist outburst of Chinese radicalism within a global context, showing that the Cultural Revolution was mirrored in the radical youth movement that swept much of the world, and that had imagined or emotional links to China's red guards. Yet it was also during the Cultural Revolution that China and the United States tempered their long hostility, one of the innovations in this period that sowed the seeds for China's subsequent decades of spectacular economic growth.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    

    Plants have also become essential to humans not only in the form of cereal crops, fruit, and vegetables, but in their many other uses in wood and paper, and in providing medicines. In this Very Short Introduction Timothy Walker, Director of the Botanical Gardens in Oxford, provides a concise account of the nature of plants, their variety and classification, their evolution, and their aesthetic and practical value, stressing the need for their conservation for future generations.

    Agnosticism emerges here as a much more sophisticated, and much more interesting, attitude than a simple failure to either commit to, or reject, religious belief. Le Poidevin challenges the common wisdom about agnosticism among both believers and atheists, and invites the reader to rethink their own position on the issues. Indeed, in arguing in favor of agnosticism as a respectable position to take, this stimulating and provocative guide takes issue on many points with the assertions of prominent atheists such as Richard Dawkins.

    This insight raises big questions about the nature of music and the nature of humankind, and ethnomusicologists argue that to properly address these questions, we must study music in all its geographical and historical diversity.In this Very Short Introduction, one of the foremost ethnomusicologists, Timothy Rice, offers a compact and illuminating account of this growing discipline, showing how modern researchers go about studying music from around the world, looking for insights into both music and humanity. The reader discovers that ethnomusicologists today not only examine traditional forms of music-such as Japanese gagaku, Bulgarian folk music, Javanese gamelan, or Native American drumming and singing-but also explore more contemporary musical forms, from rap and reggae to Tex-Mex, Serbian turbofolk, and even the piped-in music at the Mall of America. To investigate these diverse musical forms, Rice shows, ethnomusicologists typically live in a community, participate in and observe and record musical events, interview the musicians, their patrons, and the audience, and learn to sing, play, and dance. It's important to establish rapport with musicians and community members, and obtain the permission of those they will work with closely over the course of many months and years. We see how the researcher analyzes the data to understand how a particular musical tradition works, what is distinctive about it, and how it bears the personal, social, and cultural meanings attributed to it. Rice also discusses how researchers may apply theories from anthropology and other social sciences, to shed further light on the nature of music as a human behavior and cultural practice.About the Series: Oxford's Very Short Introductions series offers concise and original introductions to a wide range of subjects--from Islam to Sociology, Politics to Classics, Literary Theory to History, and Archaeology to the Bible. Not simply a textbook of definitions, each volume in this series provides trenchant and provocative--yet always balanced and complete--discussions of the central issues in a given discipline or field. Every Very Short Introduction gives a readable evolution of the subject in question, demonstrating how the subject has developed and how it has influenced society. Eventually, the series will encompass every major academic discipline, offering all students an accessible and abundant reference library. Whatever the area of study that one deems important or appealing, whatever the topic that fascinates the general reader, the Very Short Introductions series has a handy and affordable guide that will likely prove indispensable.

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    These themes include mathematical reasoning, combinatorial analysis, discrete structures, algorithmic thinking, and enhanced problem-solving skills through modeling. Its intent is to demonstrate the relevance and practicality of discrete mathematics to all students. The Fifth Edition includes a more thorough and linear presentation of logic, proof types and proof writing, and mathematical reasoning. This enhanced coverage will provide students with a solid understanding of the material as it relates to their immediate field of study and other relevant subjects. The inclusion of applications and examples to key topics has been significantly addressed to add clarity to every subject. True to the Fourth Edition, the text-specific web site supplements the subject matter in meaningful ways, offering additional material for students and instructors. Discrete math is an active subject with new discoveries made every year. The continual growth and updates to the web site reflect the active nature of the topics being discussed. The book is appropriate for a one- or two-term introductory discrete mathematics course to be taken by students in a wide variety of majors, including computer science, mathematics, and engineering. College Algebra is the only explicit prerequisite.

    Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

    It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

    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.

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.