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.

    Mirroring his theory, Minsky boldly casts The Society of Mind as an intellectual puzzle whose pieces are assembled along the way. Each chapter -- on a self-contained page -- corresponds to a piece in the puzzle. As the pages turn, a unified theory of the mind emerges, like a mosaic. Ingenious, amusing, and easy to read, The Society of Mind is an adventure in imagination.

    Wolfram lets the world see his work in A New Kind of Science, a gorgeous, 1,280-page tome more than a decade in the making. With patience, insight, and self-confidence to spare, Wolfram outlines a fundamental new way of modeling complex systems. On the frontier of complexity science since he was a boy, Wolfram is a champion of cellular automata--256 "programs" governed by simple nonmathematical rules. He points out that even the most complex equations fail to accurately model biological systems, but the simplest cellular automata can produce results straight out of nature--tree branches, stream eddies, and leopard spots, for instance. The graphics in A New Kind of Science show striking resemblance to the patterns we see in nature every day. Wolfram wrote the book in a distinct style meant to make it easy to read, even for nontechies; a basic familiarity with logic is helpful but not essential. Readers will find themselves swept away by the elegant simplicity of Wolfram's ideas and the accidental artistry of the cellular automaton models. Whether or not Wolfram's revolution ultimately gives us the keys to the universe, his new science is absolutely awe-inspiring. --Therese Littleton

    

    In 1935, aged 22, he developed the mathematical theory upon which all subsequent stored-program digital computers are modeled.At the outbreak of hostilities with Germany in September 1939, he joined the Government Codebreaking team at Bletchley Park, Buckinghamshire and played a crucial role in deciphering Engima, the code used by the German armed forces to protect their radio communications. Turing's work on the versionof Enigma used by the German navy was vital to the battle for supremacy in the North Atlantic. He also contributed to the attack on the cyphers known as Fish, which were used by the German High Command for the encryption of signals during the latter part of the war. His contribution helped toshorten the war in Europe by an estimated two years.After the war, his theoretical work led to the development of Britain's first computers at the National Physical Laboratory and the Royal Society Computing Machine Laboratory at Manchester University.Turing was also a founding father of modern cognitive science, theorizing that the cortex at birth is an unorganized machine which through training becomes organized into a universal machine or something like it. He went on to develop the use of computers to model biological growth, launchingthe discipline now referred to as Artificial Life.The papers in this book are the key works for understanding Turing's phenomenal contribution across all these fields. The collection includes Turing's declassified wartime Treatise on the Enigma; letters from Turing to Churchill and to codebreakers; lectures, papers, and broadcasts which opened upthe concept of AI and its implications; and the paper which formed the genesis of the investigation of Artifical Life.

    

    This completely updated edition brings you all the latest information about LaTeX and the vast range of add-on packages now available--over 200 are covered! Full of new tips and tricks for using LaTeX in both traditional and modern typesetting, this book will also show you how to customize layout features to your own needs--from phrases and paragraphs to headings, lists, and pages. Inside, you will find: Expert advice on using LaTeX's basic formatting tools to create all types of publications--from memos to encyclopedias In-depth coverage of important extension packages for tabular and technical typesetting, floats and captions, multicolumn layouts--including reference guides and discussions of the underlying typographic and TeXnical concepts Detailed techniques for generating and typesetting contents lists, bibliographies, indexes, etc. Tips and tricks for LaTeX programmers and systems support New to this edition: Nearly 1,000 fully tested examples that illustrate the text and solve typographical and technical problems--all ready to run! An additional chapter on citations and bibliographies Expanded material on the setup and use of fonts to access a huge collection of glyphs, and to typeset text from a wide range of languages and cultures Major new packages for graphics, "verbatim" listings, floats, and page layout Full coverage of the latest packages for all types ofdocuments--mathematical, multilingual, and many more Detailed help on all error messages, including those troublesome low-level TeX errors Like its predecessor, The LaTeX Companion, Second Edition, is an indispensable reference for anyone wishing to use LaTeX productively. The accompanying CD-ROM contains a complete plug-and-play LaTeX installation, including all the packages and examples featured in the book.

     They are also used in countless industries such as medicine, manufacturing and finance to help companies make better decisions and reduce risk. Whether coded or scratched out by hand, both algorithms are powerful tools that can make a significant impact. This book is a visual introduction for beginners that unpacks the fundamentals of decision trees and random forests. If you want to dig into the basics with a visual twist plus create your own machine learning algorithms in Python, this book is for you.

    Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.

    But they couldn't get investors interested. Today, Android is a large team at Google, shipping an operating system (including camera software) to over three billion devices worldwide.This is the inside story, told by the people who made it happen.“What are the essential ingredients that lead a small team to build software at the sheer scale and impact of Android? We may never fully know, but this first person account is probably the closest set of clues we have.”–Dave Burke, VP of Android Engineering“Androids captures a strong picture of what the early development of Android, as well as the Android team, was like.”–Dianne Hackborn, Android Framework Engineer“Androids is the engaging tale of a motley group of coders with a passion to make insanely great products who banged out the operating system when that idea seemed nuts.True to his geek genes, Chet Haase tells this remarkable tale of technical and business success from the trenches, an inspiring, massive collective effort of dozens of programmers who flipped their seemingly late timing to their advantage, and presaged a generation of platform builders. Read Androids to discover what it takes to create a hot tech team that shipped a product running today on more than 3 billion devices.”–Jonathan Littman, co-author of The Entrepreneurs Faces: How Makers, Visionaries and Outsiders Succeed, and author of The Fugitive Game

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

    The new edition features additional styles and functions, improved font handling, and enhanced graphics capabilities. Other parts of the book have been revised to reflect user comments and suggestions. Selected sections have been rewritten to explain challenging concepts or functions, and the descriptions of both MakeIndex and BibTEX have been updated. New LATEX users will want to start with this book, and current users, particularly as they upgrade to the LATEX2e software, will be eager to obtain the most up-to-date version of its associated manual. Features Revised version of the authoritative user's guide and reference manual for the LATEX computer typesetting system. Features the new standard software release - LATEX2e. Sections rewritten to explain difficult concepts or functions.

    "Programming Entity Framework, 1st Edition" offers experienced developers a thorough introduction to Microsoft's core framework for modeling and interacting with data in .NET applications. This hands-on tour provides a deep understanding of Entity Framework's architecture and APIs, and explains how to use the framework in a variety of applications built with Visual Studio 2008 and .NET 3.5.From the Entity Data Model (EDM) and Object Services to EntityClient and the Metadata Workspace, this highly acclaimed first edition covers it all.Understand the core concepts you need to make the best use of the Entity Framework (EF) in your applicationsLearn to query your data, using either LINQ to Entities or Entity SQLCreate Windows Forms, WPF, and ASP.NET applicationsBuild ASMX web services and WCF servicesUse Object Services to work directly with your entity objectsDelve into model customization, relationship management, change tracking, data concurrency, and moreOne important note: while many of the lessons from this book will continue to be valuable as you move to .NET 4, the thoroughly revised second edition of "Programming Entity Framework" (August 2010) specifically targets Visual Studio 2010 and .NET 4 -- where there have been many advancements and additions to the framework.

    By following the many programming examples included in the book and in the exercise sets, readers will gain a significant understanding of object-oriented techniques and will see how C++ can be an effective software development tool. HIGHLIGHTS *Presents file structures techniques, including direct access I/O, buffer packing and unpacking, indexing, cosequential processing, B-trees, and external hashing. *Includes extensive coverage of secondary storage devices, including disk, tape, and CD-ROM. *Covers the practice of object-oriented design and programming with complete implementations in C++. Every line of code in the book has been tested on a variety of C++ systems and is available on the Internet. *Develops a collection of C++ classes that provide a framework for solving file structure problems. *Includes class definitions, sample applications and programming problems and exercises, making this book a valuable learning and reference tool. ** Instructors materials are available from your sales rep. If you do not know your local sales representative, p

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.