This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    The preeminent expert in his field, Mr.Black draws upon years of experience as president of both theInternational and American Software Testing Qualifications boardsto offer this extensive resource of all the standards, methods, andtools you'll need.The book covers core testing concepts and thoroughly examinesthe best test management practices and tools of leading hardwareand software vendors. Step-by-step guidelines and real-worldscenarios help you follow all necessary processes and avoidmistakes.Producing high-quality computer hardware and software requirescareful, professional testing; Managing the Testing Process, Third Edition explains how to achieve that by following adisciplined set of carefully managed and monitored practices andprocessesThe book covers all standards, methods, and tools you need forprojects large and smallPresents the business case for testing products and reviews theauthor's latest test assessmentsTopics include agile testing methods, risk-based testing, IEEEstandards, ISTQB certification, distributed and outsourced testing, and moreOver 100 pages of new material and case studies have been addedto this new editionIf you're responsible for managing testing in the real world, Managing the Testing Process, Third Edition is the valuablereference and guide you need.

    Fortunately, results from the relatively new science of human visual perception provide valuable guidance. In Visual Thinking for Design, Colin Ware takes what we now know about perception, cognition, and attention and transforms it into concrete advice that designers can directly apply. He demonstrates how designs can be considered as tools for cognition - extensions of the viewer’s brain in much the same way that a hammer is an extension of the user’s hand. Experienced professional designers and students alike will learn how to maximize the power of the information tools they design for the people who use them.• Presents visual thinking as a complex process that can be supported in every stage using specific design techniques.• Provides practical, task-oriented information for designers and software developers charged with design responsibilities.• Includes hundreds of examples, many in the form of integrated text and full-color diagrams.• Steeped in the principles of “active vision,” which views graphic designs as cognitive tools.

    Python is easy to learn, and it's perfect for exploring topics like statistics, geometry, probability, and calculus. You’ll learn to write programs to find derivatives, solve equations graphically, manipulate algebraic expressions, even examine projectile motion.Rather than crank through tedious calculations by hand, you'll learn how to use Python functions and modules to handle the number crunching while you focus on the principles behind the math. Exercises throughout teach fundamental programming concepts, like using functions, handling user input, and reading and manipulating data. As you learn to think computationally, you'll discover new ways to explore and think about math, and gain valuable programming skills that you can use to continue your study of math and computer science.If you’re interested in math but have yet to dip into programming, you’ll find that Python makes it easy to go deeper into the subject—let Python handle the tedious work while you spend more time on the math.

    Madhusudhan Konda provides an overview of these, including strings in switch statements, multi-catch exception handling, try-with-resource statements, the new File System API, extensions of the JVM, support for dynamically-typed languages, and the fork and join framework for task parallelism.

    The calls to ban it were more or less instant.Re:cyclists is the tale of what happened next, of how we have spent two centuries wheeling our way about town and country on bikes--or on two-wheeled things that vaguely resembled what we now call bikes. Michael Hutchinson picks his way through those 200 years, discovering how cycling became a kinky vaudeville act for Parisians, how it became an American business empire, and how it went on to find a unique home in the British Isles. He considers the penny-farthing riders exploring the abandoned and lonely coaching roads during the railway era, and the Victorian high-society cyclists of the 1890s bicycle craze--a time when no aristocratic house party was without bicycles and when the Prince of Wales used to give himself an illicit thrill on a weekday afternoon by watching the women's riding-school in the Royal Albert Hall.Re:cyclists looks at how cycling became the sport, the pastime and the social life of millions of ordinary people, how it grew and how it suffered through the 1960s and '70s, and how at the dawn of the twenty-first century it rose again, much changed but still ultimately just someone careering along on two wheels.

    By staying current, remaining relevant, and adapting to emerging course needs, this market-leading text has continued to define the operating systems course. This Seventh Edition not only presents the latest and most relevant systems, it also digs deeper to uncover those fundamental concepts that have remained constant throughout the evolution of today's operation systems. With this strong conceptual foundation in place, students can more easily understand the details related to specific systems. New Adaptations * Increased coverage of user perspective in Chapter 1. * Increased coverage of OS design throughout. * A new chapter on real-time and embedded systems (Chapter 19). * A new chapter on multimedia (Chapter 20). * Additional coverage of security and protection. * Additional coverage of distributed programming. * New exercises at the end of each chapter. * New programming exercises and projects at the end of each chapter. * New student-focused pedagogy and a new two-color design to enhance the learning process.

    Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.

    Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

    With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples.

    Bannon had long sensed that deep within America's soul lurked an explosive tension. Cambridge Analytica had the data to prove it, and in 2016 Bannon had a presidential campaign to use as his proving ground.Christopher Wylie might have seemed an unlikely figure to be at the center of such an operation. Canadian and liberal in his politics, he was only twenty-four when he got a job with a London firm that worked with the U.K. Ministry of Defense and was charged putatively with helping to build a team of data scientists to create new tools to identify and combat radical extremism online. In short order, those same military tools were turned to political purposes, and Cambridge Analytica was born. Wylie's decision to become a whistleblower prompted the largest data crime investigation in history. His story is both exposé and dire warning about a sudden problem born of very new and powerful capabilities. It has not only exposed the profound vulnerabilities and profound carelessness in the enormous companies that drive the attention economy, it has also exposed the profound vulnerabilities of democracy itself. What happened in 2016 was just a trial run. Ruthless actors are coming for your data, and they want to control what you think.

     Him… Elijah Johnson. As in the uber-wealthy owner of the agency. My boss. In my defense, I didn’t know who he was when I clumsily bumped into him. Um.…can you say instant attraction? His hotness practically exploding underneath the expensive suit. I’m just his employee. Not his girlfriend. Besides, I am forced to work with him if I want that promotion. Working with him is getting harder by the day though. He’s charming, powerful. But he’s no Mr. Perfect. He’s got skeletons in his closet. Our project is ending. It’s the perfect time to walk away. But why do I feel this burning desire to stick around. Can I trust my heart or will this flawed man break it?

    I don't have a callsign, not yet. I'm just a caterpillar. A baby moth.I joined up because, well, I've always wanted to pilot an ATLAS mech. What can I say? We're talking three meters of pure, mobile destructive power here. A thousand hydraulically actuated joints. Head-mounted sensor package with built in LIDAR, night vision, flash vision, zoom. Crash protection. Jump jets. Active protection countermeasures. Swappable weaponry. Deployable ballistic shield. Sound like the war machine of your dreams?It is.I finally got my chance to pilot one of these babies on a little deployment out in Mongolia.Under a rather unusual set of circumstances...CATERPILLAR WITHOUT A CALLSIGN is a 7,800 word military science-fiction story set in the ATLAS universe.ATLAS, the full-length military science-fiction novel from Isaac Hooke, is now out. To download your copy, visit: http://amzn.to/1oIndEj

    Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is enhanced by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.

    As the open source implementation of Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Many IT executives are asking pointed questions about HBase. This book provides meaningful answers, whether you’re evaluating this non-relational database or planning to put it into practice right away. Discover how tight integration with Hadoop makes scalability with HBase easier Distribute large datasets across an inexpensive cluster of commodity servers Access HBase with native Java clients, or with gateway servers providing REST, Avro, or Thrift APIs Get details on HBase’s architecture, including the storage format, write-ahead log, background processes, and more Integrate HBase with Hadoop's MapReduce framework for massively parallelized data processing jobs Learn how to tune clusters, design schemas, copy tables, import bulk data, decommission nodes, and many other tasks