Many exercises are presented to help reinforce the lessons learned, and answers to the exercises are given in a new appendix.Most of the remaining chapters are dedicated to the reference material, which describes in detail the standard features of Scheme included in the Revised$^5$ Report on Scheme and the ANSI/IEEE standard for Scheme.Numerous examples are presented throughout the introductory and reference portions of the text, and a unique set of extended example programs and applications, with additional exercises, are presented in the final chapter. Reinforcing the book's utility as a reference text are appendices that present the formal syntax of Scheme, a summary of standard forms and procedures, and a bibliography of Scheme resources.The Scheme Programming Language stands alone as an introduction to and essential reference for Scheme programmers. it is also useful as a supplementary text for any course that uses Scheme.The Scheme Programming Language is illustrated by artist Jean-Pierre Hébert, who writes Scheme programs to extend his ability to create sophisticated works of digital art.R. Kent Dybvig is Professor of Computer Science at Indiana University and principal developer of Chez Scheme.

    It also covers MySQL, and PostgreSQL. It contains examples which have been tested against each SQL platform, with incompatibilities or platform distinctives called out and explained.

    You'll learn how to create responsive, data-driven websites with PHP, MySQL, and JavaScript, regardless of whether you already know how to program. Discover how the powerful combination of PHP and MySQL provides an easy way to build modern websites complete with dynamic data and user interaction. You'll also learn how to add JavaScript to create rich Internet applications and websites.Learning PHP, MySQL, and JavaScript explains each technology separately, shows you how to combine them, and introduces valuable web programming concepts, including objects, XHTML, cookies, and session management. You'll practice what you've learned with review questions in each chapter, and find a sample social networking platform built with the elements introduced in this book. This book will help you:-Understand PHP essentials and the basics of object-oriented programming-Master MySQL, from database structure to complex queries-Create web pages with PHP and MySQL by integrating forms and other HTML features-Learn about JavaScript, from functions and event handling to accessing the Document Object Model-Use libraries and packages, including the Smarty web template system, PEAR program repository, and the Yahoo! User Interface Library -Make Ajax calls and turn your website into a highly dynamic environment-Upload and manipulate files and images, validate user input, and secure your applications

    However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art?Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.More than just a source of "recipes," this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniquesTopics and features: Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory Suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book Supplies supplementary course material for students at the associated website, http: //szeliski.org/Book/ Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You'll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization's goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures

    

    This is one of those cases. The UNIX System Administration Handbook is one of the few books we ever measured ourselves against." -From the Foreword by Tim O'Reilly, founder of O'Reilly Media "This book is fun and functional as a desktop reference. If you use UNIX and Linux systems, you need this book in your short-reach library. It covers a bit of the systems' history but doesn't bloviate. It's just straightfoward information delivered in colorful and memorable fashion." -Jason A. Nunnelley"This is a comprehensive guide to the care and feeding of UNIX and Linux systems. The authors present the facts along with seasoned advice and real-world examples. Their perspective on the variations among systems is valuable for anyone who runs a heterogeneous computing facility." -Pat Parseghian The twentieth anniversary edition of the world's best-selling UNIX system administration book has been made even better by adding coverage of the leading Linux distributions: Ubuntu, openSUSE, and RHEL. This book approaches system administration in a practical way and is an invaluable reference for both new administrators and experienced professionals. It details best practices for every facet of system administration, including storage management, network design and administration, email, web hosting, scripting, software configuration management, performance analysis, Windows interoperability, virtualization, DNS, security, management of IT service organizations, and much more. UNIX(R) and Linux(R) System Administration Handbook, Fourth Edition, reflects the current versions of these operating systems: Ubuntu(R) LinuxopenSUSE(R) LinuxRed Hat(R) Enterprise Linux(R)Oracle America(R) Solaris(TM) (formerly Sun Solaris)HP HP-UX(R)IBM AIX(R)

    Peeling Data Structures and Algorithms for (C/C++ version): * Programming puzzles for interviews * Campus Preparation * Degree/Masters Course Preparation * Instructor's * GATE Preparation * Big job hunters: Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more * Reference Manual for working people

    But the state-of-the-art has moved forward dramatically since Meyers last updated this book in 1997. (For instance, there s now STL. Design patterns. Even new functionality being added through TR1 and Boost.) So Meyers has done a top-to-bottom rewrite, identifying the 55 most valuable techniques you need now to be exceptionally effective with C++. Over half of this edition s content is new. Templates broadly impact C++ development, and you ll find them everywhere. There s extensive coverage of multithreaded systems. There s an entirely new chapter on resource management. You ll find substantial new coverage of exceptions. Much is gained, but nothing s lost: You ll find the same depth of practical insight that first made Effective C++ a classic all those years ago. Bill Camarda, from the July 2005 href="http://www.barnesandnoble.com/newslet... Only

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    New topics include managing and maintaining cellular devices, including tablets; configuring operating systems, including Windows 8, Android, and iOS; and enhanced, mobile-centered security and troubleshooting procedures. The All-in-One Exam Guide enables you to take the test with complete confidence. It also serves as a practical reference for IT support and technical personnel. Bonus electronic content includes: Practice exams with hundreds of accurate questions More than an hour of video training featuring Mike Meyers Performance-based simulations that prepare you for the performance-based questions on the exam A collection of Mike's favorite free PC tools Key Features include: Written with the “in the trenches” voice and clarity Mike Meyers is known for Features pre-assessment tests, exam tips, and “Try This!” sections to reinforce difficult topics Includes a coupon for 10% off of the exam fee, a $37 value

    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.

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them

    It takes a truly objects first approach to teaching problem solving using Java. These are complicated concepts so the book uses the development environment BlueJ to help the student's understanding. BlueJ has a strong emphasis on visualization and interaction techniques, and allows the students to manipulate objects and call methods as a first exercise. BlueJ is free and freely available, and has been developed specifically for teaching. The book is loaded with projects so that the student can really get a grip on actually solving problems; and it takes a spiral approach , introducing a topic in a simple context early on, then revisiting it later in the book to deepen understanding. It also comes with a CD containing JDK, BlueJ, a BlueJ tutorial and code for all the projects. The website contains style guide for all examples, PowerPoints for lecturers and also a Solutions Manual.