Daniel Liang teaches concepts of problem-solving and object-oriented programming using a fundamentals-first approach. Beginning programmers learn critical problem-solving techniques then move on to grasp the key concepts of object-oriented and GUI programming using Java 5. Students start with the essential problem-solving and programming concepts (control statements, methods, and arrays), are then introduced to object-oriented programming, graphical user interface (GUI), and applets, and finally to exception handling, I/O, data structures, and other advanced subjects. Liang uses small, simple, and stimulating examples to demonstrate concepts and techniques while longer examples are presented in case studies with overall discussions and thorough line-by-line explanations. Students can now write short, interesting, graphical game programs starting from Chapter 2! reinforcing key concepts with objectives lists, introduction and chapter overviews, easy to follow examples, chapter summaries, review questions, programming exercises, interactive self-test. Students receive solutions to even-numbered programming exercises, source code for the examples in the book, online self assessment (w/over 1000 multiple-choice questions) and ONLINE homework through GRADIANCE, the industries most advanced online homework application. Instructors are offered the most extensive library of support materials available including interactive and animated slides, TestGen (w/over 2000 multiple-choice questions), solutions to all programming exercises, sample exams and supplemental exercises. Available in two versions, the Fundamentals First edition (chapters 1-19) and the Comprehensive version (chapters 1-36).

    Try out more than 1,000 commands to find and get software, monitor system health and security, and access network resources. Then, apply the skills you learn from this book to use and administer desktops and servers running Ubuntu, Debian, and KNOPPIX or any other Linux distribution.

     Test-Driven JavaScript Development is a complete, best-practice guide to agile JavaScript testing and quality assurance with the test-driven development (TDD) methodology. Leading agile JavaScript developer Christian Johansen covers all aspects of applying state-of-the-art automated testing in JavaScript environments, walking readers through the entire development lifecycle, from project launch to application deployment, and beyond.Using real-life examples driven by unit tests, Johansen shows how to use TDD to gain greater confidence in your code base, so you can fearlessly refactor and build more robust, maintainable, and reliable JavaScript code at lower cost. Throughout, he addresses crucial issues ranging from code design to performance optimization, offering realistic solutions for developers, QA specialists, and testers.Coverage includes - Understanding automated testing and TDD - Building effective automated testing workflows - Testing code for both browsers and servers (using Node.js) - Using TDD to build cleaner APIs, better modularized code, and more robust software - Writing testable code - Using test stubs and mocks to test units in isolation - Continuously improving code through refactoring - Walking through the construction and automated testing of fully functional softwareThe accompanying Web site, tddjs.com, contains all of the book's code listings and additional resources.

    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.

    This easy-to-read guide helps you cultivate a host of good development practices, based on classic software design patterns and new patterns unique to embedded programming. Learn how to build system architecture for processors, not operating systems, and discover specific techniques for dealing with hardware difficulties and manufacturing requirements.Written by an expert who’s created embedded systems ranging from urban surveillance and DNA scanners to children’s toys, this book is ideal for intermediate and experienced programmers, no matter what platform you use.Optimize your system to reduce cost and increase performanceDevelop an architecture that makes your software robust in resource-constrained environmentsExplore sensors, motors, and other I/O devicesDo more with less: reduce RAM consumption, code space, processor cycles, and power consumptionLearn how to update embedded code directly in the processorDiscover how to implement complex mathematics on small processorsUnderstand what interviewers look for when you apply for an embedded systems job"Making Embedded Systems is the book for a C programmer who wants to enter the fun (and lucrative) world of embedded systems. It’s very well written—entertaining, even—and filled with clear illustrations." —Jack Ganssle, author and embedded system expert.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog "AI Weirdness." She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans--all to understand the technology that governs so much of our daily lives.We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really, and how does it solve problems, understand humans, and even drive self-driving cars?Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't--like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"?In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt--and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking.

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    The language features full support for regular expressions, object-oriented modules, network programming, and process management. Perl is extensible, and supports modular, cross-platform development.In "Effective Perl Programming," Perl experts Joseph Hall and Randal Schwartz share programming solutions, techniques, programming pointers, rules of thumb, and the pitfalls to avoid, enabling you to make the most of Perl's power and capabilities.The authors will help you develop a knack for the right ways to do things. They show you how to solve problems with Perl, and how to debug and improve your Perl programs. Offering examples, they help you learn good Perl style. Geared for programmers who have already acquired Perl basics, the book will extend your skill range, providing the tactics and deeper understanding you need to create Perl programs that are more elegant, effective, and succinct. This book also speaks to those who want to become more fluent, expressive, and individualistic Perl programmers.To help you design and write effective Perl progams, Effective Perl Programming includes: Perl basics Idiomatic Perl Regular expressions Subroutines References Debugging Usage of packages and modules Object-oriented programming Useful and interesting Perl miscellanyNumerous thought-provoking examples appear throughout the book, highlighting many of the subtleties that make Perl such a fascinating, fun, and effective language to work with.

    Actually, it's computer sense--C programming. After digesting C For Dummies, 2nd Edition, you'll understand it. C programs are fast, concise and versatile. They let you boss your computer around for a change. So turn on your computer, get a free compiler and editor (the book tells you where), pull up a chair, and get going. You won't have to go far (page 13) to find your first program example. You'll do short, totally manageable, hands-on exercises to help you make sense of:All 32 keywords in the C language (that's right--just 32 words) The functions--several dozen of them Terms like printf(), scanf(), gets (), and puts () String variables, numeric variables, and constants Looping and implementation Floating-point values In case those terms are almost as intimidating as the idea of programming, be reassured that C For Dummies was written by Dan Gookin, bestselling author of DOS For Dummies, the book that started the whole library. So instead of using expletives and getting headaches, you'll be using newly acquired skills and getting occasional chuckles as you discover how to:Design and develop programs Add comments (like post-it-notes to yourself) as you go Link code to create executable programs Debug and deploy your programs Use lint, a common tool to examine and optimize your code A helpful, tear-out cheat sheet is a quick reference for comparison symbols, conversion characters, mathematical doodads, C numeric data types, and more. C For Dummies takes the mystery out of programming and gets you into it quickly and painlessly.

    Drawing on Lopp's management experiences at Apple, Netscape, Symantec, and Borland, this book is full of stories based on companies in the Silicon Valley where people have been known to yell at each other. It is a place full of dysfunctional bright people who are in an incredible hurry to find the next big thing so they can strike it rich and then do it all over again. Among these people are managers, a strange breed of people who through a mystical organizational ritual have been given power over your future and your bank account.Whether you're an aspiring manager, a current manager, or just wondering what the heck a manager does all day, there is a story in this book that will speak to you.

    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.

    However, according to Hofstadter, the formal system that underlies all mental activity transcends the system that supports it. If life can grow out of the formal chemical substrate of the cell, if consciousness can emerge out of a formal system of firing neurons, then so too will computers attain human intelligence. Gödel, Escher, Bach is a wonderful exploration of fascinating ideas at the heart of cognitive science: meaning, reduction, recursion, and much more.

    With jokes, puns, and a rigorous problem solving based approach. You can download all the code samples used in the book from here: http://www.robmiles.com/s/Yellow-Book...