Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.

    Instead of wandering through loads of theory, we will understand CSS more practically so that we can design a webpage using CSS. We have used Notepad for the examples in this book. Alternatively, you can also use Notepad++ or any advanced editor. All that you need to do is copy the code and paste it into Notepad. Upon execution, you will get the output as depicted in the screenshots. Screenshots are provided for each sample code. Coding gets better with practice. The examples in this book are compatible with almost every browser. Instead of using the verbatim code, you can modify the code and see the change in the output, thereby understanding the subtle nuances of CSS. By the end of the book, with practice, you can achieve better things and get more acquainted with CSS.

    It offers a comprehensive and accessible treatment of the theory of algorithms and complexity—the elegant body of concepts and methods developed by computer scientists over the past 30 years for studying the performance and limitations of computer algorithms. The book is self-contained in that it develops all necessary mathematical prerequisites from such diverse fields such as computability, logic, number theory and probability.

    In this new edition, the authors explain how SQL Server 2008 R2 provides a collection of powerful new tools that extend the power of its BI toolset to Excel and SharePoint users and they show how to use SQL Server to build a successful data warehouse that supports the business intelligence requirements that are common to most organizations. Covering the complete suite of data warehousing and BI tools that are part of SQL Server 2008 R2, as well as Microsoft Office, the authors walk you through a full project lifecycle, including design, development, deployment and maintenance.Features more than 50 percent new and revised material that covers the rich new feature set of the SQL Server 2008 R2 release, as well as the Office 2010 release Includes brand new content that focuses on PowerPivot for Excel and SharePoint, Master Data Services, and discusses updated capabilities of SQL Server Analysis, Integration, and Reporting Services Shares detailed case examples that clearly illustrate how to best apply the techniques described in the book The accompanying Web site contains all code samples as well as the sample database used throughout the case studies The Microsoft Data Warehouse Toolkit, Second Edition provides you with the knowledge of how and when to use BI tools such as Analysis Services and Integration Services to accomplish your most essential data warehousing tasks.

    This volume offers thorough, balanced, and practical coverage of both software and hardware topics. Develops basic concepts using the 8088 and 8086 microprocessors, but the 32-bit version of the 80x86 family is also discussed. Examines how to assemble, run, and debug programs, and how to build, test, and troubleshoot interface circuits. Provides detailed coverage of floating-point processing and the single instruction multiple data (DIMD) processing capability of the advanced Pentium processor. Includes added material on number systems, logic functions and operations, conversion between number systems, and addition/subtraction of binary numbers. Includes new advanced material such as floating Point Architecture and Instructions, Multimedia (MMX) Architecture and Instructions, and the hardware and hardware architecture of the Pentium 3 and Pentium 4 processors. Covers the Intel architecture microprocessor families: 8088, 8086, 80286, 80386, 80486, and the latest Pentium(R) processors. Illustrates commands of the DEBUG program and how to assemble, disassemble, load, save, execute, and debug programs on the IBM PC. Introduces the contents of the 8088's instruction set. Explores practical implementation techniques, covering the use of latches, transceivers, buffers, and programmable logic devices in the memory and I/O interfaces of the microcomputer system. A valuable handbook for self-study in learning microprocessors, for electrical engineers, electronic technicians, and all computer programmers.

    As a professional C++ developer and former Harvard teaching fellow, I know what you need to know to be a great C++ programmer, and I know how to teach it, one step at a time. I know where people struggle, and why, and how to make it clear. I cover every step of the programming process, including:Getting the tools you need to program and how to use them*Basic language feature like variables, loops and functions*How to go from an idea to code*A clear, understandable explanation of pointers*Strings, file IO, arrays, references*Classes and advanced class design*C++-specific programming patterns*Object oriented programming*Data structures and the standard template library (STL)Key concepts are reinforced with quizzes and over 75 practice problems.

    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

    Simply stated, it asks whether every problem whose solution can be quickly checked by computer can also be quickly solved by computer. The Golden Ticket provides a nontechnical introduction to P-NP, its rich history, and its algorithmic implications for everything we do with computers and beyond. Lance Fortnow traces the history and development of P-NP, giving examples from a variety of disciplines, including economics, physics, and biology. He explores problems that capture the full difficulty of the P-NP dilemma, from discovering the shortest route through all the rides at Disney World to finding large groups of friends on Facebook. The Golden Ticket explores what we truly can and cannot achieve computationally, describing the benefits and unexpected challenges of this compelling problem.

    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.

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    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.

    . . . Put this one on your must-have list if you have software, love software, hate programmers, or even ARE a programmer, because Mr. Platt (who teaches programming) has set out to puncture the bloated egos of all those who think that just because they can write a program, they can make it easy to use. . . . This book is funny, but it is also an important wake-up call for software companies that want to reduce the size of their customer support bills. If you were ever stuck for an answer to the question, 'Why do good programmers make such awful software?' this book holds the answer."--John McCormick, Locksmith columnist, TechRepublic.com "I must say first, I don't get many computing manuscripts that make me laugh out loud. Between the laughs, Dave Platt delivers some very interesting insight and perspective, all in a lucid and engaging style. I don't get much of that either!"--Henry Leitner, assistant dean for information technology andsenior lecturer on computer science, Harvard University "A riotous book for all of us downtrodden computer users, written in language that we understand."--Stacy Baratelli, author's barber "David's unique take on the problems that bedevil software creation made me think about the process in new ways. If you care about the quality of the software you create or use, read this book."--Dave Chappell, principal, Chappell & Associates "I began to read it in my office but stopped before I reached the bottom of the first page. I couldn't keep a grin off my face! I'll enjoy it after I go back home and find a safe place to read."--Tsukasa Makino, IT manager "David explains, in terms that my mother-in-law can understand, why the software we use today can be so frustrating, even dangerous at times, and gives us some real ideas on what we can do about it."--Jim Brosseau, Clarrus Consulting Group, Inc. A Book for Anyone Who Uses a Computer Today...and Just Wants to Scream! Today's software sucks. There's no other good way to say it. It's unsafe, allowing criminal programs to creep through the Internet wires into our very bedrooms. It's unreliable, crashing when we need it most, wiping out hours or days of work with no way to get it back. And it's hard to use, requiring large amounts of head-banging to figure out the simplest operations.It's no secret that software sucks. You know that from personal experience, whether you use computers for work or personal tasks. In this book, programming insider David Platt explains why that's the case and, more importantly, why it doesn't have to be that way. And he explains it in plain, jargon-free English that's a joy to read, using real-world examples with which you're already familiar. In the end, he suggests what you, as a typical user, without a technical background, can do about this sad state of our software--how you, as an informed consumer, don't have to take the abuse that bad software dishes out.As you might expect from the book's title, Dave's expose is laced with humor--sometimes outrageous, but always dead on. You'll laugh out loud as you recall incidents with your own software that made you cry. You'll slap your thigh with the same hand that so often pounded your computer desk and wished it was a bad programmer's face. But Dave hasn't written this book just for laughs. He's written it to give long-overdue voice to your own discovery--that software does, indeed, suck, but it shouldn't.

    But the principles and practices of software architecting–what the authors call the “science of hard decisions”–have been evolving for cloud, mobile, and other shifts. Now fully revised and updated, this book shares the knowledge and real-world perspectives that enable you to design for success–and deliver more successful solutions. In this fully updated Second Edition, you will: Learn how only a deep understanding of domain can lead to appropriate architecture Examine domain-driven design in both theory and implementation Shift your approach to code first, model later–including multilayer architecture Capture the benefits of prioritizing software maintainability See how readability, testability, and extensibility lead to code quality Take a user experience (UX) first approach, rather than designing for data Review patterns for organizing business logic Use event sourcing and CQRS together to model complex business domains more effectively Delve inside the persistence layer, including patterns and implementation.

    The book teaches a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.