Economics, finance, business & management

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    A logical, expert, easy-to-use plan for achieving excellence in expression, Style offers neither simplistic rules nor endless lists of dos and don'ts. Rather, Joseph Williams explains how to be concise, how to be focused, how to be organized. Filled with realistic examples of good, bad, and better writing, and step-by-step strategies for crafting a sentence or organizing a paragraph, Style does much more than teach mechanics: it helps anyone who must write clearly and persuasively transform even the roughest of drafts into a polished work of clarity, coherence, impact, and personality."Buy Williams's book. And dig out from storage your dog-eared old copy of The Elements of Style. Set them side by side on your reference shelf."—Barbara Walraff, Atlantic"Let newcoming writers discover this, and let their teachers and readers rejoice. It is a practical, disciplined text that is also a pleasure to read."—Christian Century"An excellent book....It provides a sensible, well-balanced approach, featuring prescriptions that work."—Donald Karzenski, Journal of Business Communication"Intensive fitness training for the expressive mind."—Booklist(The college textbook version, Style: Ten Lessons in Clarity and Grace, 9th edition, is available from Longman. ISBN 9780321479358.)

    But it's not cool to talk like a geek. Even a Geek Can Speak shows anyone how to express complex ideas in ways that are simple, that connect with listeners, and that persuade. Focusing Your Message: One internet security executive won over non-technical business owners by focusing on the importance of internet security to the business world. Result: Listeners said - I'm buying that stock.Keeping it Simple: A software consultant steered clear of the technical details when pitching to a CEO and focused on three key points: saving money, security and competitiveness. Result: He won the business.Telling Stories: A telecommunications saleswoman spoke to a users' group and illustrated her points with stories, rather than dwelling too much in detail. Result: A jump in new orders.Not Looking Like a Geek: An internet executive learned to connect with his audience merely by energizing his voice. Result: He received praise unlike any he'd received before.

    Practical Algebra is an easy andfun-to-use workout program that quickly puts you in command of allthe basic concepts and tools of algebra. With the aid of practical, real-life examples and applications, you'll learn: * The basic approach and application of algebra to problemsolving * The number system (in a much broader way than you have known itfrom arithmetic) * Monomials and polynomials; factoring algebraic expressions; howto handle algebraic fractions; exponents, roots, and radicals;linear and fractional equations * Functions and graphs; quadratic equations; inequalities; ratio, proportion, and variation; how to solve word problems, andmore Authors Peter Selby and Steve Slavin emphasize practical algebrathroughout by providing you with techniques for solving problems ina wide range of disciplines--from engineering, biology, chemistry, and the physical sciences, to psychology and even sociology andbusiness administration. Step by step, Practical Algebra shows youhow to solve algebraic problems in each of these areas, then allowsyou to tackle similar problems on your own, at your own pace.Self-tests are provided at the end of each chapter so you canmeasure your mastery.

    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.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Covering all of the fundamentals in a straightforward, student-friendly manner, it is ideal for undergraduate- and graduate-level courses across the social sciences and also serves as an indispensable guide for researchers. Striking a balance between specific techniques and the underlying logic of scientific inquiry, this book provides a lucid treatment of the four major approaches to research: experimentation, survey research, field research, and the use of available data. Richly developed examples of empirical research and an emphasis on the research process enable students to better understand the real-world application of research methods. The authors also offer a unique chapter (13) advocating a multiple-methods strategy.

    He kept a day-by-day journal of his overland journey. Abbey provides a wealth of information about what it was like to travel overland by wagon in 1850.

    Only one man knew everything about Ronnie and Reggie Kray and that was their brother Charlie. Until now nobody has ever revealed the truth about the Firm.- Gossip and rumor have been rife, fact has blended into fiction and the unwritten law of the street meant that the real story was buried. But before his death, the eldest Kray brother, Charlie, decided to set the record straight once and for all. Revealing everything to Colin Fry, his co-author, he finally told his incredible story. By the man who knew them best, this is the ultimate history of the twins who ruled the East End with their peculiar blend of seductive glamour and terrifying violence.

    Part comedy of manners, part social commentary, love story, mystic narration and thriller, it is a sort of Indian version of Oliver Goldsmith's THE VICAR OF WAKEFIELD.

    It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

    In Rules of Play Katie Salen and Eric Zimmerman present a much-needed primer for this emerging field. They offer a unified model for looking at all kinds of games, from board games and sports to computer and video games. As active participants in game culture, the authors have written Rules of Play as a catalyst for innovation, filled with new concepts, strategies, and methodologies for creating and understanding games. Building an aesthetics of interactive systems, Salen and Zimmerman define core concepts like play, design, and interactivity. They look at games through a series of eighteen game design schemas, or conceptual frameworks, including games as systems of emergence and information, as contexts for social play, as a storytelling medium, and as sites of cultural resistance.Written for game scholars, game developers, and interactive designers, Rules of Play is a textbook, reference book, and theoretical guide. It is the first comprehensive attempt to establish a solid theoretical framework for the emerging discipline of game design.

    Rather than relying on abstract generalizations and theories, van Manen offers an alternative that taps the unique nature of each human situation.The book offers detailed methodological explications and practical examples of hermeneutic-phenomenological inquiry. It shows how to orient oneself to human experience in education and how to construct a textual question which evokes a fundamental sense of wonder, and it provides a broad and systematic set of approaches for gaining experiential material that forms the basis for textual reflections.Van Manen also discusses the part played by language in educational research, and the importance of pursuing human science research critically as a semiotic writing practice. He focuses on the methodological function of anecdotal narrative in human science research, and offers methods for structuring the research text in relation to the particular kinds of questions being studied. Finally, van Manen argues that the choice of research method is itself a pedagogic commitment and that it shows how one stands in life as an educator.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.