More importantly, this book provides a framework for thinking about computer organization and design that will enable the reader to continue the lifetime of learning necessary for staying at the forefront of this competitive discipline. --John Crawford Intel Fellow Director of Microprocessor Architecture, Intel The performance of software systems is dramatically affected by how well software designers understand the basic hardware technologies at work in a system. Similarly, hardware designers must understand the far reaching effects their design decisions have on software applications. For readers in either category, this classic introduction to the field provides a deep look into the computer. It demonstrates the relationship between the software and hardware and focuses on the foundational concepts that are the basis for current computer design. Using a distinctive learning by evolution approach the authors present each idea from its first principles, guiding readers through a series of worked examples that incrementally add more complex instructions until they ha

    Internet and World Wide Web How to Program, 4e introduces students with little or no programming experience to the exciting world of Web-Based applications. The book has been substantially revised to reflect today's Web 2.0 rich Internet application-development methodologies. A comprehensive book that teaches the fundamentals needed to program on the Internet, this text provides in-depth coverage of introductory programmming principles, various markup languages (XHTML, Dynamic HTML and XML), several scripting languages (JavaScript, PHP, Ruby/Ruby on Rails and Perl); AJAX, web services, Web Servers (IIS and Apache) and relational databases (MySQL/Apache Derby/Java DB) -- all the skills and tools needed to create dynamic Web-based applications. The text contains comprehensive introductions to ASP.NET 2.0 and JavaServer Faces (JSF). Hundreds of live-code examples of real applications throughout the book available for download allow readers to run the applications and see and hear the outputs.The book provides instruction on building Ajax-enabled rich Internet applications that enhance the presentation of online content and give web applications the look and feel of desktop applications. The chapter on Web 2.0 and Internet business exposes readers to a wide range of other topics associated with Web 2.0 applications and businesses After mastering the material in this book, students will be well prepared to build real-world, industrial strength, Web-based applications.

    

     The Internet has changed the world... and, with everything from blogs to podcasts, Internet phones to video, it's still changing the world. Now, it's easy to understand how it all works! This book's big, brilliant, full-color illustrations and clear explanations make it all incredibly simple! DISCOVER HOW THE INTERNET REALLY WORKS... IT'S AMAZINGLY EASY! This new edition has been completely updated for today's hottest Internet technologies, Web connections, hardware, communications and entertainment services, and much more! - See how the Internet can deliver any kind of information, anywhere: web pages, email, music, video, phone calls, and more! - Understand the most exciting new Internet technologies, from blogs and podcasting to wikis and BitTorrent - Discover how your connection to the Internet works... wireless, cable modem, DSL, even cellphones - Go behind the scenes with today's most sophisticated websites, applications, and services - Protect yourself from the latest Internet dangers, including phishing, web surveillance, and wireless hacking Preston Gralla is the award-winning author of more than 30 books, including How the Internet Works, Complete Idiot's Guide to Internet Privacy and Security, Complete Idiot's Guide to Protecting Your Child Online, and How Wireless Works. He has written frequently about security issues, computer technology, the Internet, and has been a columnist for many magazines, websites and newspapers.

    The victory of IBM's Watson on the television quiz show Jeopardy! revealed how scientists and engineers at IBM and elsewhere are pushing the boundaries of science and technology to create machines that sense, learn, reason, and interact with people in new ways to provide insight and advice.In Smart Machines, John E. Kelly III, director of IBM Research, and Steve Hamm, a writer at IBM and a former business and technology journalist, introduce the fascinating world of "cognitive systems" to general audiences and provide a window into the future of computing. Cognitive systems promise to penetrate complexity and assist people and organizations in better decision making. They can help doctors evaluate and treat patients, augment the ways we see, anticipate major weather events, and contribute to smarter urban planning. Kelly and Hamm's comprehensive perspective describes this technology inside and out and explains how it will help us conquer the harnessing and understanding of "big data," one of the major computing challenges facing businesses and governments in the coming decades. Absorbing and impassioned, their book will inspire governments, academics, and the global tech industry to work together to power this exciting wave in innovation.

    *A comprehensive overview of hardware and software issues make this a "must-have" for electrical and computer engineers*Contains new material on RISC processors, performance analysis, multiprocessors and memory systems*New two-color design and illustrations illuminate the text

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    The emphasis throughout is on fundamental concepts--readers learn important ideas, not minor language differences--but several languages are highlighted in sufficient detail to enable readers to write programs that demonstrate the relationship between a source program and its execution behavior--e.g., C, C++, JAVA, ML, LISP, Prolog, Smalltalk, Postscript, HTML, PERL, FORTRAN, Ada, COBOL, BASIC SNOBOL4, PL/I, Pascal. Begins with a background review of programming languages and the underlying hardware that will execute the given program; then covers the underlying grammatical model for programming languages and their compilers (elementary data types, data structures and encapsulation, inheritance, statements, procedure invocation, storage management, distributed processing, and network programming). Includes an advanced chapter on language semantics--program verification, denotational semantics, and the lambda calculus. For computer engineers and others interested in programming language designs.

    Johnson. It was the first book exclusively on the theory of NP-completeness and computational intractability. The book features an appendix providing a thorough compendium of NP-complete problems (which was updated in later printings of the book). The book is now outdated in some respects as it does not cover more recent development such as the PCP theorem. It is nevertheless still in print and is regarded as a classic: in a 2006 study, the CiteSeer search engine listed the book as the most cited reference in computer science literature.

    Beginners and intermediate developers will appreciate the comprehensive tutorial that walks step-by-step through building a real client/server database, from concept to deployment and beyond -- and points out key pitfalls to avoid throughout the process. Experienced users will appreciate the book's comprehensive coverage of the Transact-SQL language, from basic to advanced level; detailed ODBC database access information; expert coverage of concurrency control, and more. The book includes thorough, up-to-the-minute guidance on building multi-tier applications; SQL Server performance tuning; and other crucial issues for advanced developers. For all database developers, system administrators, and Web application developers who interact with databases in Microsoft-centric environments.

    With this book, discover how to get the best sound for your money, how to identify the weak links in your system and upgrade where it will do the most good, how to set up and tweak your system for maximum performance, and how to become a more perceptive and appreciative listener. Just a few of the secrets you will learn cover high-end sound on a budget, how to do it cheap and still do it right; five system set-up mistakes and how to avoid them; how to make your speakers sound up to 50% better, at no cost; how to choose and set up a computer-based music system; how to find the one speaker in 50 worth owning; and why all 100-watt amplifiers don't sound the same. Since the first edition's publication in 1994, The Complete Guide to High-End Audio has been considered the essential reference on high-quality music reproduction, with more than 150,000 copies sold in five languages.

    The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In the second edition, besides revisions to the first edition, a number of new exercises have been added.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.