Yet, today’s young people have much more to offer. If half of the hipster stereotype is a consumer who tries to show off how cool he is based on his tastes, the other half of the stereotype is ‘The Maker’ -- the person out hawking homemade cheese, knitting sweaters for your beard, or repurposing steel-framed bicycles. The hipster business model is distinctive: Make a product you love so much that you’ll make it yourself. See if anyone wants it. Try again. When they want to build apparel companies, they teach themselves how to sew. When they dream of producing toys, they learn how to use 3D printing software. When they don’t know investors who will back their restaurant concepts, they open food trucks. All the while, they are guided by books, instructional videos, and intuition; only later do they move production to real factories, or hire lawyers. They frequent public parks to see if anyone will buy their custom, typewritten stories. They use crowdfunding websites to raise money from customers before their products even exist. They post their ideas to massive web forums to gauge interest, or set up online shops the second they have a product to sell. In their world, sales come first, not last. While each entrepreneur featured in this book embarked on his or her own unique quest, their stories share a common thread: like true hipsters, they were not afraid to try new things.

    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.

    Through computers, the Internet, the media, and even our daily newspapers, we are awash in a seemingly endless stream of charts, maps, infographics, diagrams, and data. Visual Explanations is a navigational guide through this turbulent sea of information. The book is an essential reference for anyone involved in graphic, web, or multimedia design, as well as for educators and lecturers who use graphics in presentations or classes.Jacket design: Dmitry Krasny.Other artwork by Bonnie Scranton, Dmitry Krasny, and Weilin Wu.

    It has made countless new businesses possible and presents a massive opportunity for large enterprises to innovate like startups and retire decades of technical debt. But making the most of the cloud requires much more from enterprises than just a technology change. Stephen Orban led Dow Jones’s journey toward digital agility as their CIO and now leads AWS’s Enterprise Strategy function, where he helps leaders from the largest companies in the world transform their businesses. As he demonstrates in this book, enterprises must re-train their people, evolve their processes, and transform their cultures as they move to the cloud. By bringing together his experiences and those of a number of business leaders, Orban shines a light on what works, what doesn’t, and how enterprises can transform themselves using the cloud.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    Instead of giving you the most broadly popular result, Google now tries to predict what you are most likely to click on. According to MoveOn.org board president Eli Pariser, Google's change in policy is symptomatic of the most significant shift to take place on the Web in recent years - the rise of personalization. In this groundbreaking investigation of the new hidden Web, Pariser uncovers how this growing trend threatens to control how we consume and share information as a society-and reveals what we can do about it.Though the phenomenon has gone largely undetected until now, personalized filters are sweeping the Web, creating individual universes of information for each of us. Facebook - the primary news source for an increasing number of Americans - prioritizes the links it believes will appeal to you so that if you are a liberal, you can expect to see only progressive links. Even an old-media bastion like "The Washington Post" devotes the top of its home page to a news feed with the links your Facebook friends are sharing. Behind the scenes a burgeoning industry of data companies is tracking your personal information to sell to advertisers, from your political leanings to the color you painted your living room to the hiking boots you just browsed on Zappos.In a personalized world, we will increasingly be typed and fed only news that is pleasant, familiar, and confirms our beliefs - and because these filters are invisible, we won't know what is being hidden from us. Our past interests will determine what we are exposed to in the future, leaving less room for the unexpected encounters that spark creativity, innovation, and the democratic exchange of ideas.While we all worry that the Internet is eroding privacy or shrinking our attention spans, Pariser uncovers a more pernicious and far-reaching trend on the Internet and shows how we can - and must - change course. With vivid detail and remarkable scope, The Filter Bubble reveals how personalization undermines the Internet's original purpose as an open platform for the spread of ideas and could leave us all in an isolated, echoing world.

    But this book is different from all the others.Becoming Steve Jobs takes on and breaks down the existing myth and stereotypes about Steve Jobs. The conventional, one-dimensional view of Jobs is that he was half-genius, half-jerk from youth, an irascible and selfish leader who slighted friends and family alike. Becoming Steve Jobs answers the central question about the life and career of the Apple cofounder and CEO: How did a young man so reckless and arrogant that he was exiled from the company he founded become the most effective visionary business leader of our time, ultimately transforming the daily life of billions of people?Drawing on incredible and sometimes exclusive access, Schlender and Tetzeli tell a different story of a real human being who wrestled with his failings and learned to maximize his strengths over time. Their rich, compelling narrative is filled with stories never told before from the people who knew Jobs best, and who decided to open up to the authors, including his family, former inner circle executives, and top people at Apple, Pixar and Disney, most notably Tim Cook, Jony Ive, Eddy Cue, Ed Catmull, John Lasseter, Robert Iger and many others. In addition, Brent knew Jobs personally for 25 years and draws upon his many interviews with him, on and off the record, in writing the book. He and Rick humanize the man and explain, rather than simply describe, his behavior. Along the way, the book provides rich context about the technology revolution we all have lived through, and the ways in which Jobs changed our world.Schlender and Tetzeli make clear that Jobs's astounding success at Apple was far more complicated than simply picking the right products: he became more patient, he learned to trust his inner circle, and discovered the importance of growing the company incrementally rather than only shooting for dazzling game-changing products.A rich and revealing account that will change the way we view Jobs, Becoming Steve Jobs shows us how one of the most colorful and compelling figures of our times was able to combine his unchanging, relentless passion with a more mature management style to create one of the most valuable and beloved companies on the planet.

    Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data.A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business dataUpdates that incorporate input from readers, changes in the field, and more material on statistics and machine learningDozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projectsComplete classroom support for instructors at www.mkp.com/datamining2e companion site

    Kai-Fu Lee—one of the world’s most respected experts on AI and China—reveals that China has suddenly caught up to the US at an astonishingly rapid and unexpected pace.In AI Superpowers, Kai-Fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power.Most experts already say that AI will have a devastating impact on blue-collar jobs. But Lee predicts that Chinese and American AI will have a strong impact on white-collar jobs as well. Is universal basic income the solution? In Lee’s opinion, probably not.  But he provides a clear description of which jobs will be affected and how soon, which jobs can be enhanced with AI, and most importantly, how we can provide solutions to some of the most profound changes in human history that are coming soon.

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    Over fifty checklists are included to take you through a structured KPI implementations process step by step. The book also includes download links for free instant access to all the templates used.

    In a world saturated with marketing messages, making your offering relevant is your biggest challenge. Dentsu's Cross Switch model meets it head on.The Dentsu Way shares proven tactics for getting your message to consumers and creating scenarios to move them through calibrated Contact Points to meet whatever specific goal you set.This game-changing book:Explains Dentsu's 110-year history and unique service structure, as well as its broad range of business fieldsIntroduces ten case studies of successful campaigns, which have won international advertising awards at events such as the Cannes Lions International Advertising Festival and ADFESTProvides nine of Dentsu's newest original tools and analysis methodsGain broader, more meaningful customer involvement and penetrate more deeply than ever into your market by following the Dentsu Way.

    This book provides an applications-oriented introduction to multivariate data analysis for the non-statistician, by focusing on the fundamental concepts that affect the use of specific techniques.

    Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problemsEach chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer supportThe authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data miningMore advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data miningCovers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis