This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    The esteemed historian Robert O. Paxton answers this question for the first time by focusing on the concrete: what the fascists did, rather than what they said. From the first violent uniformed bands beating up “enemies of the state,” through Mussolini’s rise to power, to Germany’s fascist radicalization in World War II, Paxton shows clearly why fascists came to power in some countries and not others, and explores whether fascism could exist outside the early-twentieth-century European setting in which it emerged. The Anatomy of Fascism will have a lasting impact on our understanding of modern European history, just as Paxton’s classic Vichy France redefined our vision of World War II. Based on a lifetime of research, this compelling and important book transforms our knowledge of fascism–“the major political innovation of the twentieth century, and the source of much of its pain.”

    The term “complexity” can be misleading, however, because what makes West’s discoveries so beautiful is that he has found an underlying simplicity that unites the seemingly complex and diverse phenomena of living systems, including our bodies, our cities and our businesses. Fascinated by issues of aging and mortality, West applied the rigor of a physicist to the biological question of why we live as long as we do and no longer. The result was astonishing, and changed science, creating a new understanding of energy use and metabolism: West found that despite the riotous diversity in the sizes of mammals, they are all, to a large degree, scaled versions of each other. If you know the size of a mammal, you can use scaling laws to learn everything from how much food it eats per day, what its heart-rate is, how long it will take to mature, its lifespan, and so on. Furthermore, the efficiency of the mammal’s circulatory systems scales up precisely based on weight: if you compare a mouse, a human and an elephant on a logarithmic graph, you find with every doubling of average weight, a species gets 25% more efficient—and lives 25% longer. This speaks to everything from how long we can expect to live to how many hours of sleep we need. Fundamentally, he has proven, the issue has to do with the fractal geometry of the networks that supply energy and remove waste from the organism's body. West's work has been game-changing for biologists, but then he made the even bolder move of exploring his work's applicability to cities. Cities, too, are constellations of networks and laws of scalability relate with eerie precision to them. For every doubling in a city's size, the city needs 15% less road, electrical wire, and gas stations to support the same population. More amazingly, for every doubling in size, cities produce 15% more patents and more wealth, as well as 15% more crime and disease. This broad pattern lays the groundwork for a new science of cities. Recently, West has applied his revolutionary work on cities and biological life to the business world. This investigation has led to powerful insights into why some companies thrive while others fail. The implications of these discoveries are far-reaching, and are just beginning to be explored. Scale is a thrilling scientific adventure story about the elemental natural laws that bind us together in simple but profound ways. Through the brilliant mind of Geoffrey West, we can envision how cities, companies and biological life alike are dancing to the same simple, powerful tune, however diverse and unrelated they are to each other.From the Hardcover edition.

    It gives a clear and authoritative guide to the general framework of network analysis, explaining the basic concepts, technical measures and reviewing the available computer programs.The book outlines both the theoretical basis of network analysis and the key techniques for using it as a research tool. Building upon definitions of points, lines and paths, John Scott demonstrates their use in clarifying such measures as density, fragmentation and centralization. He identifies the various cliques, components and circles into which networks are formed, and outlines

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    Since 2001, newspaper and music revenues have fallen by 70%, book publishing, film and television profits have also fallen dramatically. Revenues at Google in this same period grew from $400 million to $74.5 billion. Google's YouTube today controls 60% of the streaming audio business and pays only 11% of the streaming audio revenues. More creative content is being consumed than ever before, but less revenue is flowing to creators and owners of the content.With the reallocation of money to monopoly platforms comes a shift in power. Google, Facebook, and Amazon now enjoy political power on par with Big Oil and Big Pharma, which in part explains how such a tremendous shift in revenues from artists to platforms could have been achieved and why it has gone unchallenged for so long.The stakes in this story go far beyond the livelihood of any one musician or journalist. As Taplin observes, the fact that more and more Americans receive their news, music and other forms of entertainment from a small group of companies poses a real threat to democracy. Move Fast and Break Things offers a vital, forward-thinking prescription for how artists can reclaim their audiences using knowledge of the past and a determination to work together. Using his own half-century career as a music and film producer and early pioneer of streaming video online, Taplin offers new ways to think about the design of the World Wide Web and specifically the way we live with the firms that dominate it.Table of contentsIntroduction1. The Great Disruption2. Levon's Story3. Tech's Counterculture Roots4. The Libertarian Counterinsurgency5. Digital Destruction6. Monopoly in the Digital Age7. Google's Regulatory Capture8. The Social Media Revolution9. Pirates of the Internet10. Libertarian and the 1 Percent11. What It Means to Be Human12. The Digital RenaissanceAfterword

    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

    He then jets forward to the nineteenth century, where systems we can easily recognize as modern bureaucracies come into being. In some areas of life—like with the modern postal systems of Germany and France—these bureaucracies have brought tremendous efficiencies to modern life. But Graeber argues that there is a much darker side to modern bureaucracy that is rarely ever discussed. Indeed, in our own “utopia of rules,” freedom and technological innovation are often the casualties of systems that we only faintly understand.Provocative and timely, the book is a powerful look and history of bureaucracy over the ages and its power in shaping the world of ideas.

    Published posthumously in Germany in the early 1920's, it has become a constitutive part of the modern sociological imagination. Economy and Society was the first strictly empirical comparison of social structures and normative orders in world-historical depth, containing the famous chapters on social action, religion, law, bureaucracy, charisma, the city, and the political community with its dimensions of class, status and power.Economy and Status is Weber's only major treatise for an educated general public. It was meant to be a broad introduction, but in its own way it is the most demanding textbook yet written by a sociologist. The precision of its definitions, the complexity of its typologies and the wealth of its historical content make the work a continuos challenge at several levels of comprehension: for the advanced undergraduate who gropes for his sense of society, for the graduate student who must develop his own analytical skills, and for the scholar who must match wits with Weber.When the long-awaited first complete English edition of Economy and Society was published in 1968, Arthur Stinchcombe wrote in the American Journal of Sociology: "My answer to the question of whether people should still start their sociological intellectual biographies with Economy and Society is yes." Reinhard Bendix noted in the American Sociological Review that the "publication of a compete English edition of Weber's most systematic work [represents] the culmination of a cultural transmission to the American setting...It will be a study-guide and compendium for years to come for all those interested in historical sociology and comparative study."In a lengthy introduction, Guenther Roth traces the intellectual prehistory of Economy and Society, the gradual emergence of its dominant themes and the nature of its internal logic.Mr. Roth is a Professor of Sociology at Columbia University. Mr. Wittich heads an economic research group at the United Nations.

    In her study of the state of modern humanity, Hannah Arendt considers humankind from the perspective of the actions of which it is capable. The problems Arendt identified then--diminishing human agency and political freedom; the paradox that as human powers increase through technological and humanistic inquiry, we are less equipped to control the consequences of our actions—continue to confront us today.

    But few of us realize just how many oversights, biases, and downright ethical nightmares are baked inside the tech products we use every day. It’s time we change that.In Technically Wrong, Sara Wachter-Boettcher demystifies the tech industry, leaving those of us on the other side of the screen better prepared to make informed choices about the services we use—and to demand more from the companies behind them.

    Bayesian statistics is taught in most first-year statistics classes across the nation, but there is one major problem that many students (and others who are interested in the theorem) face. The theorem is not intuitive for most people, and understanding how it works can be a challenge, especially because it is often taught without visual aids. In this guide, we unpack the various components of the theorem and provide a basic overview of how it works - and with illustrations to help. Three scenarios - the flu, breathalyzer tests, and peacekeeping - are used throughout the booklet to teach how problems involving Bayes Theorem can be approached and solved. Over 60 hand-drawn visuals are included throughout to help you work through each problem as you learn by example. The illustrations are simple, hand-drawn, and in black and white. For those interested, we have also included sections typically not found in other beginner guides to Bayes Rule. These include: A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios.A few examples of how to think like a Bayesian in everyday life. Bayes Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. It is a great tool that can help you with critical thinking, problem-solving, and dealing with the gray areas of life. A concise history of Bayes Rule. Bayes Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700’s to its being used to break the German’s Enigma Code during World War 2, its tale is quite phenomenal.Fascinating real-life stories on how Bayes formula is used in everyday life.From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life. We have summed up 3 examples for you and provided an example of how Bayes could be used.An expanded definitions, notations, and proof section.We have included an expanded definitions and notations sections at the end of the booklet. In this section we define core terms more concretely, and also cover additional terms you might be confused about. A recommended readings section.From The Theory That Would Not Die to a few other books, there are a number of recommendations we have for further reading. Take a look! If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you. Bayesian statistics is an incredibly fascinating topic and likely touches your life every single day. It is a very important tool that is used in data analysis throughout a wide-range of industries - so take an easy dive into the theorem for yourself with a visual approach!If you are looking for a short beginners guide packed with visual examples, this booklet is for you.

    One of the great promises of the Internet and big data revolutions is the idea that we can improve the processes and routines of our work and personal lives to get more done in less time than ever before. There is no doubt that we're performing at higher scales and going faster than ever, but what if we're headed in the wrong direction?The Efficiency Paradox questions our ingrained assumptions about efficiency, persuasively showing how relying on the algorithms of platforms can in fact lead to wasted efforts, missed opportunities, and above all an inability to break out of established patterns. Edward Tenner offers a smarter way to think about efficiency, showing how we can combine artificial intelligence and our own intuition, leaving ourselves and our institutions open to learning from the random and unexpected.

    Using a layout style that was later copied by Wired, McLuhan and coauthor/designer Quentin Fiore combine word and image to illustrate and enact the ideas that were first put forward in the dense and poorly organized Understanding Media. McLuhan's ideas about the nature of media, the increasing speed of communication, and the technological basis for our understanding of who we are come to life in this slender volume. Although originally printed in 1967, the art and style in The Medium is the Massage seem as fresh today as in the summer of love, and the ideas are even more resonant now that computer interfaces are becoming gateways to the global village.

    Five actual journal articles are reproduced in the appendix as examples of the different research designs.