Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Landes's acclaimed, best-selling exploration of one of the most contentious and hotly debated questions of our time: Why do some nations achieve economic success while others remain mired in poverty? The answer, as Landes definitively illustrates, is a complex interplay of cultural mores and historical circumstance. Rich with anecdotal evidence, piercing analysis, and a truly astonishing range of erudition, The Wealth and Poverty of Nations is a "picture of enormous sweep and brilliant insight" (Kenneth Arrow) as well as one of the most audaciously ambitious works of history in decades.For the paperback edition, Landes has written a new epilogue, in which he takes account of Asian financial crisises and the international tension between overconfidence and reality.

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    The new edition provides invitations - not requirements - to use technology, as well as new conceptual problems, and new projects that focus on writing and working in teams.

    For introductory courses in computer concepts or computer literacy often including instruction in Microsoft Office.A Computer Concepts Text Focused on Today’s Student!Technology in Action engages students by combining a unique teaching approach with rich companion media.

    Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps readers discover the nature of statistics and understand its essential role in scientific research.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    Drive-up ATM keypads have Braille dots because it's cheaper to make the same machine for both drive-up and walk-up locations. Travelers from Kansas City to Orlando pay less because they are usually price-sensitive tourists with many choices of destination, whereas travelers originating from Orlando typically choose Kansas City for specific family or business reasons.The Economic Naturalist employs basic economic principles to answer scores of intriguing questions from everyday life, and, along the way, introduces key ideas such as the cost benefit principle, the "no cash left on the table" principle, and the law of one price. There is no more delightful and painless way of learning these fundamental principles.

    This author team is known for their outstanding research, teaching efforts, and world-renowned finance textbooks, so it's no surprise that they provide clear exposition of difficult material without sacrificing up-to-date, technically correct treatments. The seventh edition has been fully updated to reflect recent events and is now available with Connect Finance! Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, and how they need it, so that your class time is more engaging and effective.

    Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong."Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.In this book, you'll learn: - Why "statistically significant" doesn't necessarily imply practical significance- Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas- How and how not to ask questions, design experiments, and work with data- Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates- Why false positives are much more common than "significant at the 5% level" would suggestBy walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, "Statistics Done Wrong" will teach you how to be a better analyst, data scientist, or researcher.

    Visually engaging, enticing and current examples with an overall focus on business.Legal Environment of Business and E-Commerce; Torts, Crimes, and Intellectual Property; Contracts and E-Commerce; Domestic and International Sales and Lease Contracts; Negotiable Instruments and E-Money; Credit, Secured Transactions, and Bankruptcy; Agency and Employment; Business Organizations and Ethics; Government Regulation; Property; Special Topics; Global EnvironmentMARKET Business Law continues its dedication to being the most engaging text for readers by featuring a visually appealing format with enticing and current examples while maintaining its focus on business.

    While such visualizations can better inform us, they can also deceive by displaying incomplete or inaccurate data, suggesting misleading patterns—or simply misinform us by being poorly designed, such as the confusing “eye of the storm” maps shown on TV every hurricane season.Many of us are ill equipped to interpret the visuals that politicians, journalists, advertisers, and even employers present each day, enabling bad actors to easily manipulate visuals to promote their own agendas. Public conversations are increasingly driven by numbers, and to make sense of them we must be able to decode and use visual information. By examining contemporary examples ranging from election-result infographics to global GDP maps and box-office record charts, How Charts Lie teaches us how to do just that.

    Friedman, the Pulitzer Prize-winning foreign affairs columnist for The New York Times, offers an engrossing look at the new international system that is transforming world affairs today. Globalization has replaced the Cold War system with the integration of capital, technology, and information across national borders—uniting Brazilian peasants, Indonesian entrepreneurs, Chinese villagers, and Silicon Valley technocrats in a single global village. You cannot understand the morning news, know where to invest your money, or think about the future unless you understand this new system, which is profoundly influencing virtually every country in the world today. Friedman tells you what this electronic global economy is all about and what it will take to live within it.With vivid stories drawn from his extensive travels, he dramatizes the conflict of “the Lexus and the olive tree”—the tension between the globalization system and the ancient forces of culture, geography, tradition, and community. He also details the powerful backlash that globalization produces among those who feel brutalized by it, and he spells out what we all need to do to keep the Lexus and the olive tree in balance. For this new paperback edition, Friedman has substantially expanded and updated his provocative analysis, making it essential reading for all who care about how the world works now.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Now revised and updated to include expanded coverage of monetary policy, this volume traces the history of macroeconomics and the evolution of macroeconomic thought and the resulting theory and policy.