Introducing students to the many facets of neural networks, this text provides many case studies to illustrate their real-life, practical applications.

    Written by the creator of Minux, professional programmers will now have the most up-to-date tutorial and reference available today. Revised to address the latest version of MINIX (MINIX 3), this streamlined, simplified new edition remains the only operating systems text to first explain relevant principles, then demonstrate their applications using a Unix-like operating system as a detailed example. It has been especially designed for high reliability, for use in embedded systems, and for ease of teaching.

    We are promised that apps, algorithms, and artificial intelligence will relieve congestion, restore democracy, prevent crime, and improve public services. In The Smart Enough City, Ben Green warns against seeing the city only through the lens of technology; taking an exclusively technical view of urban life will lead to cities that appear smart but under the surface are rife with injustice and inequality. He proposes instead that cities strive to be "smart enough" to embrace technology as a powerful tool when used in conjunction with other forms of social change--but not to value technology as an end in itself.In a technology-centric smart city, self-driving cars have the run of downtown and force out pedestrians, civic engagement is limited to requesting services through an app, police use algorithms to justify and perpetuate racist practices, and governments and private companies surveil public space to control behavior. Green describes smart city efforts gone wrong but also smart enough alternatives, attainable with the help of technology but not reducible to technology: a livable city, a democratic city, a just city, a responsible city, and an innovative city. By recognizing the complexity of urban life rather than merely seeing the city as something to optimize, these Smart Enough Cities successfully incorporate technology into a holistic vision of justice and equity.

    The book gives more than it promises, the text as well as the extensive bibliography including contributions of the analysts."-Hibbert Journal

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    

    Each chapter applies a different theory to case examples and - to provide continuity - to a fictitious client' constructed from many past clients of the authors.

    It offers a battery of methods that can be used to help us understand human behavior. Nevertheless, the legitimacy of this exercise is at the center of a heated controversy that has raged for over a century. Many evolutionary biologists, anthropologists and psychologists have taken these evolutionary principles and tried using them to explain a wide range of human characteristics, such as homicide, religion and sex differences in behavior. Others, however, are sceptical of these interpretations. Moreover, researchers disagree as to the best ways to use evolution to explore humanity, and a number of schools have emerged. Sense and Nonsense provides an introduction to the ideas, methods, and findings of five such schools, namely, sociobiology, human behavioural ecology, evolutionary psychology, memetics, and gene-culture co-evolution. Carefully guiding the reader through the mire of confusing terminology, claim and counter-claim, and polemical statements, Laland and Brown provide a balanced, rigorous analysis that scrutinizes both the evolutionary arguments and the allegations of the critics. This is a book that will be make fascinating reading for popular science readers, undergraduate and postgraduate students (for example, in psychology, anthropology and zoology), and to experts on one approach who would like to know more about the other perspectives. Having completed this book the reader will feel better placed to assess the legitimacy of claims made about human behavior under the name of evolution, and to make judgements as to what is sense and what is nonsense.

    Linear algebra is tightly integrated into the text.

    The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout. Author resource page: http: //www.stat.columbia.edu/ gelman/arm/

    It is suitable for a one or two semester university course on AI, as well as for researchers in the field.

    KEY TOPICS: This classic book enables readers to make connections between classical and modern physics - an indispensable part of a physicist's education. In this new edition, Beams Medal winner Charles Poole and John Safko have updated the book to include the latest topics, applications, and notation, to reflect today's physics curriculum. They introduce readers to the increasingly important role that nonlinearities play in contemporary applications of classical mechanics. New numerical exercises help readers to develop skills in how to use computer techniques to solve problems in physics. Mathematical techniques are presented in detail so that the book remains fully accessible to readers who have not had an intermediate course in classical mechanics. MARKET: For college instructors and students.

    One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

    It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.

    The Roman empire in the west was splitting into separate Germanic kingdoms, while the Near East, still under Roman rule from Constantinople, maintained a dense population and flourishing urban culture until the Persian and Arab invasions of the early seventh century. Averil Cameron places her emphasis on the material and literary evidence for cultural change and offers a new and original challenge to traditional assumptions of 'decline and fall' and 'the end of antiquity'. The book draws on the recent spate of scholarship on this period to discuss in detail such controversial issues as the effectiveness of the late Roman army, the late antique city and the nature of economic exchange and cultural life. With its extensive annotation, it provides a lively and often critical introduction to earlier approaches to the period, from Edward Gibbon's Decline and Fall of the Roman Empire to the present day. No existing book in English provides so detailed or up-to-date an introduction to the history of both halves of the empire in this crucial period, or discusses existing views in such a challenging way. Averil Cameron is a leading specialist on late antiquity, having written about the period and taught it for many years. This book has much to say to historians of all periods. It will be particularly welcomed by teachers and students of both ancient and medieval history.