With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    We take advantage of this revolutionary opportunity when we make our work "open access" digital, online, free of charge, and free of most copyright and licensing restrictions. Open access is made possible by the Internet and copyright-holder consent, and many authors, musicians, filmmakers, and other creators who depend on royalties are understandably unwilling to give their consent. But for 350 years, scholars have written peer-reviewed journal articles for impact, not for money, and are free to consent to open access without losing revenue.In this concise introduction, Peter Suber tells us what open access is and isn't, how it benefits authors and readers of research, how we pay for it, how it avoids copyright problems, how it has moved from the periphery to the mainstream, and what its future may hold. Distilling a decade of Suber's influential writing and thinking about open access, this is the indispensable book on the subject for researchers, librarians, administrators, funders, publishers, and policy makers.ContentsSeries Foreword viiPreface ix1 What Is Open Access? 12 Motivation 293 Varieties 494 Policies 775 Scope 976 Copyright 1257 Economics 1338 Casualties 1499 Future 16310 Self-Help 169Glossary 175Notes 177Additional Resources 219Index 223

    It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.Data Visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "small multiple" plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings.Provides hands-on instruction using R and ggplot2Shows how the "tidyverse" of data analysis tools makes working with R easier and more consistentIncludes a library of data sets, code, and functions

    Your colleague's husband's sister can make you fat, even if you don't know her. A happy neighbor has more impact on your happiness than a happy spouse. These startling revelations of how much we truly influence one another are revealed in the studies of Dr. Christakis and Fowler, which have repeatedly made front-page news nationwide. In Connected, the authors explain why emotions are contagious, how health behaviors spread, why the rich get richer, even how we find and choose our partners. Intriguing and entertaining, Connected overturns the notion of the individual and provides a revolutionary paradigm-that social networks influence our ideas, emotions, health, relationships, behavior, politics, and much more. It will change the way we think about every aspect of our lives.

    It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

    Why did work become so miserable? Who is responsible? And does any company have a model for doing it right?For two years, Lyons ventured in search of answers. From the innovation-crazed headquarters of the Ford Motor Company in Detroit, to a cult-like "Holocracy" workshop in San Francisco, and to corporate trainers who specialize in ... Legos, Lyons immersed himself in the often half-baked and frequently lucrative world of what passes for management science today. He shows how new tools, workplace practices, and business models championed by tech's empathy-impaired power brokers have shattered the social contract that once existed between companies and their employees. These dystopian beliefs--often masked by pithy slogans like "We're a Team, Not a Family"--have dire consequences: millions of workers who are subject to constant change, dehumanizing technologies--even health risks. A few companies, however, get it right. With Lab Rats, Lyons makes a passionate plea for business leaders to understand this dangerous transformation, showing how profit and happy employees can indeed coexist.

    It is one of the fastest growing companies in history, an essential part of the social life not only of teenagers but hundreds of millions of adults worldwide. As Facebook spreads around the globe, it creates surprising effects—even becoming instrumental in political protests from Colombia to Iran. Veteran technology reporter David Kirkpatrick had the full cooperation of Facebook’s key executives in researching this fascinating history of the company and its impact on our lives. Kirkpatrick tells us how Facebook was created, why it has flourished, and where it is going next. He chronicles its successes and missteps, and gives readers the most complete assessment anywhere of founder and CEO Mark Zuckerberg, the central figure in the company’s remarkable ascent. This is the Facebook story that can be found nowhere else. How did a nineteen-year-old Harvard student create a company that has transformed the Internet and how did he grow it to its current enormous size? Kirkpatrick shows how Zuckerberg steadfastly refused to compromise his vision, insistently focusing on growth over profits and preaching that Facebook must dominate (his word) communication on the Internet. In the process, he and a small group of key executives have created a company that has changed social life in the United States and elsewhere, a company that has become a ubiquitous presence in marketing, altering politics, business, and even our sense of our own identity. This is the Facebook Effect.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    In his classic The Age of Spiritual Machines, he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: the union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

    With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Spark’s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

    He was also producing for the ear. In the audiobook version of Talking to Strangers, you'll hear the voices of people he interviewed--scientists, criminologists, military psychologists. Court transcripts are brought to life with re-enactments. You actually hear the contentious arrest of Sandra Bland by the side of the road in Texas. As Gladwell revisits the deceptions of Bernie Madoff, the trial of Amanda Knox, and the suicide of Sylvia Plath, you hear directly from many of the players in these real-life tragedies. There's even a theme song - Janelle Monae's "Hell You Talmbout."Something is very wrong, Gladwell argues, with the tools and strategies we use to make sense of people we don't know. And because we don't know how to talk to strangers, we are inviting conflict and misunderstanding in ways that have a profound effect on our lives and our world.

    With this concise book, you will learn how to use the latest version of this W3C standard to retrieve and manipulate the increasing amount of public and private data available via SPARQL endpoints. Several open source and commercial tools already support SPARQL, and this introduction gets you started right away.Begin with how to write and run simple SPARQL 1.1 queries, then dive into the language's powerful features and capabilities for manipulating the data you retrieve. Learn what you need to know to add to, update, and delete data in RDF datasets, and give web applications access to this data.Understand SPARQL’s connection with RDF, the semantic web, and related specificationsQuery and combine data from local and remote sourcesCopy, convert, and create new RDF dataLearn how datatype metadata, standardized functions, and extension functions contribute to your queriesIncorporate SPARQL queries into web-based applications

    In one hundred lean and incisive statements, he argues that we are essentially social creatures, and that we achieve our greatest aspirations when we work together—not as individuals. Yet today society is threatened by a vast antihuman infrastructure that undermines our ability to connect. Money, once a means of exchange, is now a means of exploitation; education, conceived as way to elevate the working class, has become another assembly line; and the internet has only further divided us into increasingly atomized and radicalized groups.Team Human delivers a call to arms. If we are to resist and survive these destructive forces, we must recognize that being human is a team sport. In Rushkoff’s own words: “Being social may be the whole point.” Harnessing wide-ranging research on human evolution, biology, and psychology, Rushkoff shows that when we work together we realize greater happiness, productivity, and peace. If we can find the others who understand this fundamental truth and reassert our humanity—together—we can make the world a better place to be human.

    In this fascinating, provocative new book, Kevin Kelly provides an optimistic road map for the future, showing how the coming changes in our lives—from virtual reality in the home to an on-demand economy to artificial intelligence embedded in everything we manufacture—can be understood as the result of a few long-term, accelerating forces. Kelly both describes these deep trends—flowing, screening, accessing, sharing, filtering, remixing, tracking, and questioning—and demonstrates how they overlap and are codependent on one another. These larger forces will completely revolutionize the way we buy, work, learn, and communicate with each other. By understanding and embracing them, says Kelly, it will be easier for us to remain on top of the coming wave of changes and to arrange our day-to-day relationships with technology in ways that bring forth maximum benefits. Kelly’s bright, hopeful book will be indispensable to anyone who seeks guidance on where their business, industry, or life is heading—what to invent, where to work, in what to invest, how to better reach customers, and what to begin to put into place—as this new world emerges.

    Each entry deals with one fallacy, explaining what the fallacy is, giving and analysing an example, outlining when/where/why the particular fallacy tends to occur and finally showing how you can perpetrate the fallacy on other people in order to win an argument. Originally published to great acclaim in 1985 as "The Book of Fallacy", this is a classic brought up-to-date for a whole new generation.