From entertainment to politics, from technology to advertising and from science to the business world, understanding and using data is now one of the most transferable and transferable skills out there. Learning how to work with data may seem intimidating or difficult but with Confident Data Skills you will be able to master the fundamentals and supercharge your professional abilities. This essential book covers data mining, preparing data, analysing data, communicating data, financial modelling, visualizing insights and presenting data through film making and dynamic simulations.In-depth international case studies from a wide range of organizations, including Netflix, LinkedIn, Goodreads, Deep Blue, Alpha Go and Mike's Hard Lemonade Co. show successful data techniques in practice and inspire you to turn knowledge into innovation. Confident Data Skills also provides insightful guidance on how you can use data skills to enhance your employability and improve how your industry or company works through your data skills. Expert author and instructor, Kirill Eremenko, is committed to making the complex simple and inspiring you to have the confidence to develop an understanding, adeptness and love of data.

    Here, for the first time and in detail, Zimbardo tells the full story of the Stanford Prison Experiment, the landmark study in which a group of college-student volunteers was randomly divided into “guards” and “inmates” and then placed in a mock prison environment. Within a week, the study was abandoned, as ordinary college students were transformed into either brutal, sadistic guards or emotionally broken prisoners. By illuminating the psychological causes behind such disturbing metamorphoses, Zimbardo enables us to better understand a variety of harrowing phenomena, from corporate malfeasance to organized genocide to how once upstanding American soldiers came to abuse and torture Iraqi detainees in Abu Ghraib. He replaces the long-held notion of the “bad apple” with that of the “bad barrel”—the idea that the social setting and the system contaminate the individual, rather than the other way around.

    Bruno Latour's contention is that the word "social" as used by Social Scientists has become laden with assumptions to the point where it has become a misnomer. When the adjective is applied to a phenomenon, it is used to indicate a stabilized state of affairs, a bundle of ties that in due course may be used to account for another phenomenon. Latour also finds the word used as if it described a type of material, in a comparable way to an adjective such as "wooden" or "steely".Rather than simply indicating what is already assembled together, it is now used in a way that makes assumptions about the nature of what is assembled. It has become a word that designates two distinct things: a process of assembling: and a type of material, distinct from others. Latour shows why "the social" cannot be thought of as a kind of material or domain, and disputes attempts to provide a "social explanation" of other states of affairs. While these attempts have been productive (and probably necessary) in the past, the very success of the social sciences mean that they are largely no longer so. At the present stage it is no longer possible to inspect the precise constituents entering the social domain. Latour returns to the original meaning of "the social" to redefine the notion and allow it to trace connections again. It will then be possible to resume the traditional goal of the social sciences, but using more refined tools. Drawing on his extensive work examining the "assemblages" of nature, Latour finds it necessary to scrutinize thoroughly the exact content of what is assembled under the umbrella of Society. This approach, a "sociology of associations" has become known as Actor-Network-Theory, and this book is an essential introduction both for those seeking to understand Actor-Network-Theory, or the ideas of one of its most influential proponents.

    Written by the world’s foremost PowerPivot blogger and practitioner, the book’s concepts and approach are introduced in a simple, step-by-step manner tailored to the learning style of Excel users everywhere. The techniques presented allow users to produce, in hours or even minutes, results that formerly would have taken entire teams weeks or months to produce. It includes lessons on the difference between calculated columns and measures; how formulas can be reused across reports of completely different shapes; how to merge disjointed sets of data into unified reports; how to make certain columns in a pivot behave as if the pivot were filtered while other columns do not; and how to create time-intelligent calculations in pivot tables such as “Year over Year” and “Moving Averages” whether they use a standard, fiscal, or a complete custom calendar. The “pattern-like” techniques and best practices contained in this book have been developed and refined over two years of onsite training with Excel users around the world, and the key lessons from those seminars costing thousands of dollars per day are now available to within the pages of this easy-to-follow guide. This updated second edition covers new features introduced with Office 2015.

    Anthropologist Mary L. Gray and computer scientist Siddharth Suri team up to unveil how services delivered by companies like Amazon, Google, Microsoft, and Uber can only function smoothly thanks to the judgment and experience of a vast, invisible human labor force. These people doing "ghost work" make the internet seem smart. They perform high-tech piecework: flagging X-rated content, proofreading, designing engine parts, and much more. An estimated 8 percent of Americans have worked at least once in this “ghost economy,” and that number is growing. They usually earn less than legal minimums for traditional work, they have no health benefits, and they can be fired at any time for any reason, or none.There are no labor laws to govern this kind of work, and these latter-day assembly lines draw in—and all too often overwork and underpay—a surprisingly diverse range of workers: harried young mothers, professionals forced into early retirement, recent grads who can’t get a toehold on the traditional employment ladder, and minorities shut out of the jobs they want. Gray and Suri also show how ghost workers, employers, and society at large can ensure that this new kind of work creates opportunity—rather than misery—for those who do it.

    Yet, for the digital natives soon to enter the workforce, the technologies and principles behind crowdsourcing are perfectly intuitive. This generation collaborates, shares, remixes, and creates with a fluency and ease the rest of us can hardly understand. Crowdsourcing, just now starting to emerge, will in a short time simply be the way things are done.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    Ideal for introducing the novice researcher to the theory and practice of qualitative research, this text opens students to the diverse possibilities within this inquiry approach, while helping them understand how to design and implement specific research methods. The author's accessible writing style, the wealth of examples, and the numerous exercises provide opportunities for practicing and refining the skills of becoming a qualitative researcher. The new edition focuses on the development of research proposals (Ch. 2); the history and concerns of institutional review boards (IRBs) and issues qualitative researchers sometimes confront when submitting proposals (Ch. 6); greater information and examples on coding and thematic analysis, while also introducing other approaches to data analysis (Ch. 7); and arts based research through a chapter that encourages consideration of creative ways to approach and represent inquiry (Ch. 9). Chapter 10 looks at sharing research results through participation at conferences and in publications.

     Universal Methods of Design serves as an invaluable compendium of methods that can be easily referenced and used by cross-disciplinary teams in nearly any design project.   Methods and techniques are organized alphabetically for ongoing, quick reference. Each method is presented in a two-page format. The left-hand page contains a concise description of the method, accompanied by references for further reading. On the right-hand page, images and cases studies for each method are presented visually. The relevant phases for design application are highlighted as numbered icons along the right side of the page, from phases 1 (planning) through 5 (launch and monitor).Build more meaningful products with these methods and more: A/B Testing, Affinity Diagramming, Behavioral Mapping, Bodystorming, Contextual Design, Critical Incident Technique, Directed Storytelling, Flexible Modeling, Image Boards, Graffiti Walls, Heuristic Evaluation, Parallel Prototyping, Simulation Exercises, Touchstone Tours, and Weighted Matrix.  This essential guide:Dismantles the myth that user research methods are complicated, expensive, and time-consumingCreates a shared meaning for cross-disciplinary design teamsIllustrates methods with compelling visualizations and case studiesCharacterizes each method at a glanceIndicates when methods are best employed to help prioritize appropriate design research strategiesUniversal Methods of Design is an essential resource for designers of all levels and specializations.

    You might think the problem is your brain. It seems to have a mind of its own, a mind that doesn't always want to take in the dry, technical stuff you're forced to study. The fact is your brain craves novelty. It's constantly searching, scanning, waiting for something unusual to happen. After all, that's the way it was built to help you stay alive. It takes all the routine, ordinary, dull stuff and filters it to the background so it won't interfere with your brain's real work--recording things that matter. How does your brain know what matters? It's like the creators of the Head First approach say, suppose you're out for a hike and a tiger jumps in front of you, what happens in your brain? Neurons fire. Emotions crank up. Chemicals surge. That's how your brain knows.And that's how your brain will learn Java. Head First Java combines puzzles, strong visuals, mysteries, and soul-searching interviews with famous Java objects to engage you in many different ways. It's fast, it's fun, and it's effective. And, despite its playful appearance, Head First Java is serious stuff: a complete introduction to object-oriented programming and Java. You'll learn everything from the fundamentals to advanced topics, including threads, network sockets, and distributed programming with RMI. And the new. second edition focuses on Java 5.0, the latest version of the Java language and development platform. Because Java 5.0 is a major update to the platform, with deep, code-level changes, even more careful study and implementation is required. So learning the Head First way is more important than ever. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. You'll see why people say it's unlike any other Java book you've ever read.By exploiting how your brain works, Head First Java compresses the time it takes to learn and retain--complex information. Its unique approach not only shows you what you need to know about Java syntax, it teaches you to think like a Java programmer. If you want to be bored, buy some other book. But if you want to understand Java, this book's for you.

    Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on?In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate.Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business.Human + Machine provides the missing and much-needed management playbook for success in our new age of AI.

    Gigabytes, exabytes (that’s one quintillion bytes) of data are sitting on servers across the world. So how can we start to access this explosion of information, this “big data,” and what can it tell us?   Erez Aiden and Jean-Baptiste Michel are two young scientists at Harvard who started to ask those questions. They teamed up with Google to create the Ngram Viewer, a Web-based tool that can chart words throughout the massive Google Books archive, sifting through billions of words to find fascinating cultural trends. On the day that the Ngram Viewer debuted in 2010, more than one million queries were run through it.   On the front lines of Big Data, Aiden and Michel realized that this big dataset—the Google Books archive that contains remarkable information on the human experience—had huge implications for looking at our shared human history. The tool they developed to delve into the data has enabled researchers to track how our language has evolved over time, how art has been censored, how fame can grow and fade, how nations trend toward war. How we remember and how we forget. And ultimately, how Big Data is changing the game for the sciences, humanities, politics, business, and our culture.

    Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines.The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness.In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways.Written with acclaimed science writer Sandra Blakeslee, On Intelligence promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.

    But what happens when this system of adjusting emotions is adapted to commercial purposes? Hochschild examines the cost of this kind of "emotional labor." She vividly describes from a humanist and feminist perspective the process of estrangement from personal feelings and its role as an "occupational hazard" for one-third of America's workforce.

    But today, success is increasingly dependent on how we interact with others. It turns out that at work, most people operate as either takers, matchers, or givers. Whereas takers strive to get as much as possible from others and matchers aim to trade evenly, givers are the rare breed of people who contribute to others without expecting anything in return. Using his own pioneering research as Wharton's youngest tenured professor, Grant shows that these styles have a surprising impact on success. Although some givers get exploited and burn out, the rest achieve extraordinary results across a wide range of industries. Combining cutting-edge evidence with captivating stories, this landmark book shows how one of America's best networkers developed his connections, why the creative genius behind one of the most popular shows in television history toiled for years in anonymity, how a basketball executive responsible for multiple draft busts transformed his franchise into a winner, and how we could have anticipated Enron's demise four years before the company collapsed - without ever looking at a single number. Praised by bestselling authors such as Dan Pink, Tony Hsieh, Dan Ariely, Susan Cain, Dan Gilbert, Gretchen Rubin, Bob Sutton, David Allen, Robert Cialdini, and Seth Godin-as well as senior leaders from Google, McKinsey, Merck, Estee Lauder, Nike, and NASA - Give and Take highlights what effective networking, collaboration, influence, negotiation, and leadership skills have in common. This landmark book opens up an approach to success that has the power to transform not just individuals and groups, but entire organizations and communities.