Since its creation in 2010, Instagram’s fun and simple interface has captured our collective imagination, swiftly becoming a way of life. In No Filter: The Inside Story of Instagram, technology reporter Sarah Frier explains how Instagram’s founders married art and technology to overcome skeptics and to hook the public on visual storytelling. At first, Instagram initially attracted artisans, but then the platform exploded in popularity among the masses, creating an entire industry of digital influencers that’s now worth tens of billions of dollars. Eighteen months after Instagram’s launch and explosive growth, the founders—Kevin Systrom and Mike Krieger—made the gut-wrenching decision to sell the company to Facebook. For most companies, that would be the end of the story; but for Instagram, it was only the beginning. Instagram borrowed some lessons from Facebook and rejected others, until eventually its success stirred tension with Facebook’s CEO Mark Zuckerberg, just as Facebook became embroiled in a string of public crises. Frier unearths the details that led to the cofounders’ departure, bringing to light dramatic moments unknown to the public until now. At its heart, No Filter draws on unprecedented exclusive access—from the founders of Instagram, as well as employees, executives, and competitors; hedge fund billionaire Ray Dalio; Anna Wintour of Vogue; Kris Jenner of the Kardashian-Jenner empire; and a plethora of influencers, from fashionistas with millions of followers to owners of famous dogs worldwide—to show how Instagram has fundamentally changed the way we communicate, shop, eat, and travel. The book brings readers inside users’ strategies to craft their personal image and fame, explaining how the company’s product decisions have affected the structure of our society. From teenagers to the pope, No Filter tells the captivating story of how Instagram not only created a new industry but also changed our lives.

    Beginning with an introduction to array formulas, this manual examines topics such as how they differ from ordinary formulas, the benefits and drawbacks of their use, functions that can and cannot handle array calculations, and array constants and functions. Among the practical applications surveyed include how to extract data from tables and unique lists, how to get results that match any criteria, and how to utilize various methods for unique counts. This book contains 529 screen shots.

    When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls--information about the caller, the recipient, the time, the duration, the location--and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems? In this book, Jeffrey Pomerantz offers an accessible and concise introduction to metadata.In the era of ubiquitous computing, metadata has become infrastructural, like the electrical grid or the highway system. We interact with it or generate it every day. It is not, Pomerantz tell us, just "data about data." It is a means by which the complexity of an object is represented in a simpler form. For example, the title, the author, and the cover art are metadata about a book. When metadata does its job well, it fades into the background; everyone (except perhaps the NSA) takes it for granted.Pomerantz explains what metadata is, and why it exists. He distinguishes among different types of metadata--descriptive, administrative, structural, preservation, and use--and examines different users and uses of each type. He discusses the technologies that make modern metadata possible, and he speculates about metadata's future. By the end of the book, readers will see metadata everywhere. Because, Pomerantz warns us, it's metadata's world, and we are just living in it.

    Just set aside one hour a day—lunchtime would be perfect—for a month, and you'll be automating Windows tasks faster than you ever thought possible. You'll start with the basics—what is PowerShell and what can you do with it. Then, you'll move systematically through the techniques and features you'll use to make your job easier and your day shorter. This totally revised second edition covers new PowerShell 3 features designed for Windows 8 and Windows Server 2012.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.What's InsideLearn PowerShell from the beginning—no experience required! Covers PowerShell 3, Windows 8, and Windows Server 2012 Each lesson should take you one hour or lessAbout the TechnologyPowerShell is both a language and an administrative shell with which you can control and automate nearly every aspect of Windows. It accepts and executes commands immediately, and you can write scripts to manage most Windows servers like Exchange, IIS, and SharePoint.Experience with Windows administration is helpful. No programming experience is assumed.Table of ContentsBefore you begin Meet PowerShell Using the help system Running commands Working with providers The pipeline: connecting commands Adding commands Objects: data by another name The pipeline, deeper Formatting—and why it's done on the right Filtering and comparisons A practical interlude Remote control: one to one, and one to many Using Windows Management Instrumentation Multitasking with background jobs Working with many objects, one at a time Security alert! Variables: a place to store your stuff Input and output Sessions: remote control with less work You call this scripting? Improving your parameterized script Advanced remoting configuration Using regular expressions to parse text files Additional random tips, tricks, and techniques Using someone else's script Never the end PowerShell cheat sheet

    What will happen when misinformation moves from our social media feeds into our everyday lives?Online disinformation stormed our political process in 2016 and has only worsened since. Yet as Samuel Woolley shows in this urgent book, it may pale in comparison to what's to come: humanlike automated voice systems, machine learning, "deepfake" AI-edited videos and images, interactive memes, virtual reality, and more. These technologies have the power not just to manipulate our politics, but to make us doubt our eyes and ears and even feelings.Deeply researched and compellingly written, The Reality Game describes the profound impact these technologies will have on our lives. Each new invention built without regard for its consequences edges us further into this digital dystopia.Yet Woolley does not despair. Instead, he argues pointedly for a new culture of innovation, one built around accountability and especially transparency. With social media dragging us into a never-ending culture war, we must learn to stop fighting and instead prevent future manipulation. This book shows how we can use our new tools not to control people but to empower them.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me.Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

    It is also the most powerful, and in some ways, the most confusing. What do accessible, content-focused standards-based web designers and front-end developers need to know? And how can we harness the power of HTML5 in today’s browsers?In this brilliant and entertaining user’s guide, Jeremy Keith cuts to the chase, with crisp, clear, practical examples, and his patented twinkle and charm.

    Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age.How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more.An essential introduction to the new technologies of digital currencyCovers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much moreFeatures an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slidesAlso suitable for use with the authors' Coursera online courseElectronic solutions manual (available only to professors)

    Sold in over 85 countries and translated into more than 5 languages.---------------Want to get started on data science?Our promise: no math added.This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.Popular concepts covered include:- A/B Testing- Anomaly Detection- Association Rules- Clustering- Decision Trees and Random Forests- Regression Analysis- Social Network Analysis- Neural NetworksFeatures:- Intuitive explanations and visuals- Real-world applications to illustrate each algorithm- Point summaries at the end of each chapter- Reference sheets comparing the pros and cons of algorithms- Glossary list of commonly-used termsWith this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

    In barely six years, a small group of young, ambitious programmers in Silicon Valley built an $11.5 billion business out of the ashes of a failed podcasting company. Today Twitter boasts more than 200 million active users and has affected business, politics, media, and other fields in innumerable ways. Now Nick Bilton of the New York Times takes readers behind the scenes with a narrative that shows what happened inside Twitter as it grew at exponential speeds. This is a tale of betrayed friendships and high-stakes power struggles as the four founders—Biz Stone, Evan Williams, Jack Dorsey, and Noah Glass—went from everyday engineers to wealthy celebrities, featured on magazine covers, Oprah, The Daily Show, and Time’s list of the world’s most influential people. Bilton’s exclusive access and exhaustive investigative reporting—drawing on hundreds of sources, documents, and internal e-mails—have enabled him to write an intimate portrait of fame, influence, and power. He also captures the zeitgeist and global influence of Twitter, which has been used to help overthrow governments in the Middle East and disrupt the very fabric of the way people communicate.

    According to Neil Gershenfeld, the renowned MIT scientist and inventor, the next big thing is personal fabrication–the ability to design and produce your own products, in your own home, with a machine that combines consumer electronics with industrial tools. Personal fabricators (PF’s) are about to revolutionize the world just as personal computers did a generation ago. PF’s will bring the programmability of the digital world to the rest of the world, by being able to make almost anything-including new personal fabricators. In FAB, Gershenfeld describes how personal fabrication is possible today, and how it is meeting local needs with locally developed solutions. He and his colleagues have created “fab labs” around the world, which, in his words, can be interpreted to mean “a lab for fabrication, or simply a fabulous laboratory.” Using the machines in one of these labs, children in inner-city Boston have made saleable jewelry from scrap material. Villagers in India used their lab to develop devices for monitoring food safety and agricultural engine efficiency. Herders in the Lyngen Alps of northern Norway are developing wireless networks and animal tags so that their data can be as nomadic as their animals. And students at MIT have made everything from a defensive dress that protects its wearer’s personal space to an alarm clock that must be wrestled into silence. These experiments are the vanguard of a new science and a new era-an era of “post-digital literacy” in which we will be as familiar with digital fabrication as we are with the of information processing. In this groundbreaking book, the scientist pioneering the revolution in personal fabrication reveals exactly what is being done, and how. The technology of FAB will allow people to create the objects they desire, and the kind of world they want to live in.

    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

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Negroponte's fans will want to get a copy of Being Digital, which is an edited version of the 18 articles he wrote for Wired about "being digital." Negroponte's text is mostly a history of media technology rather than a set of predictions for future technologies. In the beginning, he describes the evolution of CD-ROMs, multimedia, hypermedia, HDTV (high-definition television), and more. The section on interfaces is informative, offering an up-to-date history on visual interfaces, graphics, virtual reality (VR), holograms, teleconferencing hardware, the mouse and touch-sensitive interfaces, and speech recognition. In the last chapter and the epilogue, Negroponte offers visionary insight on what "being digital" means for our future. Negroponte praises computers for their educational value but recognizes certain dangers of technological advances, such as increased software and data piracy and huge shifts in our job market that will require workers to transfer their skills to the digital medium. Overall, Being Digital provides an informative history of the rise of technology and some interesting predictions for its future.