What began more than sixty years ago as a modest proposal that a mathematician and an economist write a short paper together blossomed, in 1944, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences.This sixtieth anniversary edition includes not only the original text but also an introduction by Harold Kuhn, an afterword by Ariel Rubinstein, and reviews and articles on the book that appeared at the time of its original publication in the New York Times, tthe American Economic Review, and a variety of other publications. Together, these writings provide readers a matchless opportunity to more fully appreciate a work whose influence will yet resound for generations to come.

    Selected for originality, general interest, or because they demonstrate valuable techniques, the problems are ideal as a supplement to courses in probability or statistics, or as stimulating recreation for the mathematically minded. Detailed solutions. Illustrated.

    The study of type systems--and of programming languages from a type-theoretic perspective--has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

    Haskell emerged in the last decade as a standard for lazy functional programming, a programming style where arguments are evaluated only when the value is actually needed. Haskell is a marvellous demonstration tool for logic and maths because its functional character allows implementations to remain very close to the concepts that get implemented, while the laziness permits smooth handling of infinite data structures.This book does not assume the reader to have previous experience with either programming or construction of formal proofs, but acquaintance with mathematical notation, at the level of secondary school mathematics is presumed. Everything one needs to know about mathematical reasoning or programming is explained as we go along. After proper digestion of the material in this book the reader will be able to write interesting programs, reason about their correctness, and document them in a clear fashion. The reader will also have learned how to set up mathematical proofs in a structured way, and how to read and digest mathematical proofs written by others.

    "Using Econometrics: A Practical Guide "provides readers with a practical introduction that combines single-equation linear regression analysis with real-world examples and exercises. This text also avoids complex matrix algebra and calculus, making it an ideal text for beginners. New problem sets and added support make "Using Econometrics" modern and easier to use.

    Alphabetically organized and easy to use, its nearly 400 entries provide guidance for the most common types of professional documents and correspondence, including reports, proposals, manuals, memos, and white papers. Abundant sample documents and visuals throughout the book demonstrate effective technical communication, reflecting current practices for formatting documents and using e-mail. In addition, advice on organizing, researching, writing, and revising complements thorough treatment of grammar, usage, style, and punctuation to provide comprehensive help with writing skills. This edition has been thoroughly revised to include expanded advice for analyzing the context of different writing situations, using and integrating visuals, and dealing with ethical concerns in technical writing. Improved coverage of research now includes guidelines for IEEE-style documentation as well as clearer explanations of copyright and plagiarism concerns. Entries throughout the book have been revised, updated, consolidated, and streamlined to provide the most accurate and accessible information. Comprehensive yet concise, the Handbook of Technical Writing remains the quick reference faithful users have come to appreciate.

    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.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    For over half a century, the MLA Handbook is the guide millions of writers have relied on.The seventh edition is a comprehensive, up-to-date guide to research and writing in the online environment. It provides an authoritative update of MLA documentation style for use in student writing, including simplified guidelines for citing works published on the Web and new recommendations for citing several kinds of works, such as digital files and graphic narratives.Every copy of the seventh edition of the MLA Handbook comes with a code for accessing the accompanying Web site. New to this edition, the Web site provides- the full text of the print volume of the MLA Handbook- over two hundred additional examples- several research-project narratives--stories, with sample papers, that illustrate the steps successful students take in researching and writing papers- searching of the entire site, including the full text of the MLA Handbook- continuous access throughout the life of the seventh edition of the MLA Handbook

    You can easily access this chapter at Oreilly.com once you register your book.Your time is way too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Web Design uses a visually rich format specifically designed to take advantage of the way your brain really works.

    It provides a transition from elementary calculus to advanced courses in real and complex function theory and introduces the reader to some of the abstract thinking that pervades modern analysis.

    This bestselling Sybex study guide covers 100% of all exam objectives. You'll prepare for the exam smarter and faster with Sybex thanks to expert content, real-world examples, advice on passing each section of the exam, access to the Sybex online interactive learning environment, and much more. Reinforce what you've learned with key topic exam essentials and chapter review questions. Along with the book, you also get access to Sybex's superior online interactive learning environment that includes: Four unique 250 question practice exams to help you identify where you need to study more. Get more than 90 percent of the answers correct, and you're ready to take the certification exam. More than 650 Electronic Flashcards to reinforce your learning and give you last-minute test prep before the exam A searchable glossary in PDF to give you instant access to the key terms you need to know for the exam Coverage of all of the exam topics in the book means you'll be ready for: Security and Risk Management Asset Security Security Engineering Communication and Network Security Identity and Access Management Security Assessment and Testing Security Operations Software Development Security

    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

    and abroad, this reader-friendly yet authoritative volume bridges the gap between circuits and new electromagnetics material. Ulaby begins coverage with transmission lines, leading readers from familiar concepts into more advanced topics and applications. Includes six new sections on Waveguides and Cavity Resonators, replacing the material on geometric optics in Chapter 8. Presents new Technology Briefs on relevant topics, connecting concepts in the book to everyday applications found in real life, such as liquid crystal displays, the laser, GPS, and x-ray tomography. Includes an interactive CD-ROM that allows readers to gain physical intuition about electromagnetics. A useful reference for engineers.

    This new edition simplifies many of the steps involved in analysis by using the computer application Excel. Over 100 detailed example problems illustrate important fluid mechanics concepts: Approximately 1300 end-of-chapter problems are arranged by difficulty level and include many problems that are designed to be solved using Excel. The CD for the book includes: A Brief Review of Microsoft Excel and numerous Excel files for the example problems and for use in solving problems. The new edition includes an expanded discussion of pipe networks, and a new section on oblique shocks and expansion waves.