In Turing’s Cathedral, George Dyson focuses on a small group of men and women, led by John von Neumann at the Institute for Advanced Study in Princeton, New Jersey, who built one of the first computers to realize Alan Turing’s vision of a Universal Machine. Their work would break the distinction between numbers that mean things and numbers that do things—and our universe would never be the same. Using five kilobytes of memory (the amount allocated to displaying the cursor on a computer desktop of today), they achieved unprecedented success in both weather prediction and nuclear weapons design, while tackling, in their spare time, problems ranging from the evolution of viruses to the evolution of stars. Dyson’s account, both historic and prophetic, sheds important new light on how the digital universe exploded in the aftermath of World War II. The proliferation of both codes and machines was paralleled by two historic developments: the decoding of self-replicating sequences in biology and the invention of the hydrogen bomb. It’s no coincidence that the most destructive and the most constructive of human inventions appeared at exactly the same time.  How did code take over the world? In retracing how Alan Turing’s one-dimensional model became John von Neumann’s two-dimensional implementation, Turing’s Cathedral offers a series of provocative suggestions as to where the digital universe, now fully three-dimensional, may be heading next.

    With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas

    Learn how to retouch digital photos, work with layers and masks, navigate the workspace, prepare images print, and explore the latest features. Tips, extra-credit exercises, and step-by-step lessons help you become more productive using Photoshop. Learn to correct and enhance digital photos, create image composites, transform images in perspective, and prepare images for print and the web. Combine images for extended depth of field, and try out the new 3D features in Adobe Photoshop CS4 Extended. "The Classroom in a Book series is by far the best training material on the market. Everything you need to master the software is included: clear explanations of each lesson, step-by-step instructions, and the project files for the students." --Barbara Binder, Adobe Certified Instructor, Rocky Mountain Training Classroom in a Book(R), the best-selling series of hands-on software training workbooks, helps you learn the features of Adobe software quickly and easily. Classroom in a Book offers what no other book or training program does--an official training series from Adobe Systems Incorporated, developed with the support of Adobe product experts.

    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.

    Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.

    Along the way, we encounter black holes, turtles, snakes, dragons, axe-sharpening, and yak-shaving—and take a guided tour through the theories and methods, both brilliant and misguided, that litter the history of software development, from the famous ‘mythical man-month’ to Extreme Programming. Not just for technophiles but for anyone captivated by the drama of invention, Dreaming in Code offers a window into both the information age and the workings of the human mind.

    

    

    Although many developers feel that XP is rooted in commonsense, its vastly different approach can bring challenges, frustrations, and constant demands on your patience.Unless you've got unlimited time (and who does these days?), you can't always stop to thumb through hundreds of pages to find the piece of information you need. The Extreme Programming Pocket Guide is the answer. Concise and easy to use, this handy pocket guide to XP is a must-have quick reference for anyone implementing a test-driven development environment.The Extreme Programming Pocket Guide covers XP assumptions, principles, events, artifacts, roles, and resources, and more. It concisely explains the relationships between the XP practices. If you want to adopt XP in stages, the Extreme Programming Pocket Guide will help you choose what to apply and when. You'll be surprised at how much practical information is crammed into this slim volume.O'Reilly's Pocket Guides have become a favorite among developers everywhere. By providing a wealth of important details in a concise, well-organized format, these handy books deliver just what you need to complete the task at hand. When you've reached a sticking point in your work and need to get to a solution quickly, the new Extreme Programming Pocket Guide is the book you'll want to have beside your keyboard.

    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

    It is the only book that gives a full introduction to programming in MATLAB combined with an explanation of MATLAB's powerful functions. The book differs from other texts in that it teaches programming concepts and the use of the built-in functions in MATLAB simultaneously. It presents programming concepts and MATLAB built-in functions side-by-side, giving students the ability to program efficiently and exploit the power of MATLAB to solve problems. The systematic, step-by-step approach, building on concepts throughout the book, facilitates easier learning.Starting with basic programming concepts, such as variables, assignments, input/output, selection, and loop statements, problems are introduced and solved throughout the book. The book is organized into two parts. Part I covers the programming constructs and demonstrates programming versus efficient use of built-in functions to solve problems. Part II describes the applications, including plotting, image processing, and mathematics, needed in basic problem solving. The chapters feature sections called Quick Question! as well as practice problems designed to test knowledge about the material covered. Problems are solved using both The Programming Concept and The Efficient Method, which facilitates understanding the efficient ways of using MATLAB, and also the programming concepts used in these efficient functions and operators. There are also sections on 'common pitfalls' and 'programming guidelines' that direct students towards best practice.This book is ideal for engineers learning to program and model in MATLAB, as well as undergraduates in engineering and science taking a course on MATLAB.

    However, rather than resting on that reputation, the new edition of this text marks a significant advance in the already excellent quality of the book. While preserving concise language, state of the art educational pedagogy, and top-notch worked examples, the Eighth Edition features a unified art design as well as streamlined and carefully reorganized problem sets that enhance the thoughtful instruction for which Raymond A. Serway and John W. Jewett, Jr. earned their reputations. Likewise, PHYSICS FOR SCIENTISTS AND ENGINEERS, will continue to accompany Enhanced WebAssign in the most integrated text-technology offering available today. In an environment where new Physics texts have appeared with challenging and novel means to teach students, this book exceeds all modern standards of education from the most solid foundation in the Physics market today.

    I'm sure you'll find the read rewarding." --From the Foreword by Scott Meyers D is a programming language built to help programmers address the challenges of modern software development. It does so by fostering modules interconnected through precise interfaces, a federation of tightly integrated programming paradigms, language-enforced thread isolation, modular type safety, an efficient memory model, and more. The D Programming Language is an authoritative and comprehensive introduction to D. Reflecting the author's signature style, the writing is casual and conversational, but never at the expense of focus and pre-cision. It covers all aspects of the language (such as expressions, statements, types, functions, contracts, and modules), but it is much more than an enumeration of features. Inside the book you will find In-depth explanations, with idiomatic examples, for all language features How feature groups support major programming paradigms Rationale and best-use advice for each major feature Discussion of cross-cutting issues, such as error handling, contract programming, and concurrency Tables, figures, and "cheat sheets" that serve as a handy quick reference for day-to-day problem solving with D Written for the working programmer, The D Programming Language not only introduces the D language--it presents a compendium of good practices and idioms to help both your coding with D and your coding in general.

    And then we wonder why software is notorious for being delivered late and full of bugs, while other engineers routinely deliver finished bridges, automobiles, electrical appliances, etc., on time and with only minor defects. This book sets out to redress this imbalance. Members of my advanced development team at Adobe who took the course based on the same material all benefited greatly from the time invested. It may appear as a highly technical text intended only for computer scientists, but it should be required reading for all practicing software engineers." --Martin Newell, Adobe Fellow"The book contains some of the most beautiful code I have ever seen." --Bjarne Stroustrup, Designer of C++"I am happy to see the content of Alex's course, the development and teaching of which I strongly supported as the CTO of Silicon Graphics, now available to all programmers in this elegant little book." --Forest Baskett, General Partner, New Enterprise Associates"Paul's patience and architectural experience helped to organize Alex's mathematical approach into a tightly-structured edifice--an impressive feat!" --Robert W. Taylor, Founder of Xerox PARC CSL and DEC Systems Research Center Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.This is not an easy book. Nor is it a compilation of tips and tricks for incremental improvements in your programming skills. The book's value is more fundamental and, ultimately, more critical for insight into programming. To benefit fully, you will need to work through it from beginning to end, reading the code, proving the lemmas, and doing the exercises. When finished, you will see how the application of the deductive method to your programs assures that your system's software components will work together and behave as they must.The book presents a number of algorithms and requirements for types on which they are defined. The code for these descriptions--also available on the Web--is written in a small subset of C++ meant to be accessible to any experienced programmer. This subset is defined in a special language appendix coauthored by Sean Parent and Bjarne Stroustrup.Whether you are a software developer, or any other professional for whom programming is an important activity, or a committed student, you will come to understand what the book's experienced authors have been teaching and demonstrating for years--that mathematics is good for programming, and that theory is good for practice.

    We start off easy, defining some of the tech lingo you may have heard before, but didn’t fully understand. From there, each lesson introduces something new, slowly building up to the point where you are confident about what an API is and, for the brave, could actually take a stab at using one.