The author's take on the essence of Java as a new programming language and the thorough introduction to Java's features make this a worthwhile tutorial. Thinking in Java begins a little esoterically, with the author's reflections on why Java is new and better. (This book's choice of font for chapter headings is remarkably hard on the eyes.) The author outlines his thoughts on why Java will make you a better programmer, without all the complexity. The book is better when he presents actual language features. There's a tutorial to basic Java types, keywords, and operators. The guide includes extensive source code that is sometimes daunting (as with the author's sample code for all the Java operators in one listing.) As such, this text will be most useful for the experienced developer. The text then moves on to class design issues, when to use inheritance and composition, and related topics of information hiding and polymorphism. (The treatment of inner classes and scoping will likely seem a bit overdone for most readers.) The chapter on Java collection classes for both Java Developer's Kit (JDK) 1.1 and the new classes, such as sets, lists, and maps, are much better. There's material in this chapter that you are unlikely to find anywhere else. Chapters on exception handling and programming with type information are also worthwhile, as are the chapters on the new Swing interface classes and network programming. Although it adopts somewhat of a mixed-bag approach, Thinking in Java contains some excellent material for the object-oriented developer who wants to see what all the fuss is about with Java.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    Indeed, that's what computers are for. You can enlist your own computer to automate all of your project's repetitive tasks, ranging from individual builds and running unit tests through to full product release, customer deployment, and monitoring the system.Many teams try to do these tasks by hand. That's usually a really bad idea: people just aren't as good at repetitive tasks as machines. You run the risk of doing it differently the one time it matters, on one machine but not another, or doing it just plain wrong. But the computer can do these tasks for you the same way, time after time, without bothering you. You can transform these labor-intensive, boring and potentially risky chores into automatic, background processes that just work.In this eagerly anticipated book, you'll find a variety of popular, open-source tools to help automate your project. With this book, you will learn: How to make your build processes accurate, reliable, fast, and easy. How to build complex systems at the touch of a button. How to build, test, and release software automatically, with no human intervention. Technologies and tools available for automation: which to use and when. Tricks and tips from the masters (do you know how to have your cell phone tell you that your build just failed?) You'll find easy-to-implement recipes to automate your Java project, using the same popular style as the rest of our Jolt Productivity Award-winning Starter Kit books. Armed with plenty of examples and concrete, pragmatic advice, you'll find it's easy to get started and reap the benefits of modern software development. You can begin to enjoy pragmatic, automatic, unattended software production that's reliable and accurate every time.

    It offers on expressiveness and safety without compromising simplicity, seamless interoperability with existing Java code, and great tooling support. Because Kotlin generates regular Java bytecode and works together with existing Java libraries and frameworks, it can be used almost everywhere where Java is used today - for server-side development, Android apps, and much more.Kotlin in Action takes experienced Java developers from the language basics all the way through building applications to run on the JVM and Android devices. Written by core developers of Kotlin, this example-rich book begins by teaching you the basic syntax of the Kotlin language. Then you’ll learn how to use features that let you build reusable abstractions, higher-level functions, libraries, and even entire domain specific languages. Finally, you’ll focus on details of applying Kotlin in real-world projects, such as build system integration, Android support and concurrent programming.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

    Work at your own pace through a series of lessons and practical exercises, and then assess your skills with practice tests on CD—featuring multiple, customizable testing options.Maximize your performance on the exam by learning how to:Create database objectsWork with dataModify dataTroubleshoot and optimize queriesYou also get an exam discount voucher—making this book an exceptional value and a great career investment.

    You need to stay current on the relevant Web specifications, like HTML, CSS, DOM, and ECMAScript. You also need to know how the latest Web browsers from Netscape and Microsoft actually implement these standards, since browser implementations of the standards are less than perfect. Right now, you're forced to keep multiple reference books open on your desk (or multiple browser windows open on your screen), just to develop a simple dynamic Web page that works properly under both Navigator and Internet Explorer.Dynamic HTML: The Definitive Reference changes all that. This book is an indispensable compendium for Web content developers. It contains everything you need to create functional cross-platform Web applications, including:A complete reference for all of the HTML tags, CSS style attributes, browser document objects, and JavaScript objects supported by the various standards and the latest versions of Navigator and Internet Explorer. Browser compatibility is emphasized throughout; the reference pages clearly indicate browser support for every entity. Handy cross-reference indexes that make it easy to find interrelated HTML tags, style attributes, and document objects. An advanced introduction to creating dynamic Web content that addresses the cross-platform compromises inherent in Web page design today. If you have some experience with basic Web page creation, but are new to the world of dynamic content, Dynamic HTML: The Definitive Reference will jump-start your development efforts. If you are an experienced Web programmer, you'll find the browser-compatibility information invaluable. This book is the only DHTML reference that a Web developer needs.Dynamic HTML: The Definitive Reference is designed to work in conjunction with HTML: The Definitive Guide and JavaScript: The Definitive Guide. HTML: The Definitive Guide teaches you about every element of HTML in detail, with explanations of how each element works and how it interacts with other elements, as well as numerous examples. JavaScript: The Definitive Guide provides a thorough description of the JavaScript language, complete with sophisticated examples that show you how to handle common Web application tasks. Together, these three books provide a complete library for Web content developers.

    The result is a stunning achievement in graphics education. Through the ideas and software in this book, you will learn to design and employ a full-featured rendering system for creating stunning imagery.This new edition greatly refines its best-selling predecessor by streamlining all obsolete code as well as adding sections on parallel rendering and system design; animating transformations; multispectral rendering; realistic lens systems; blue noise and adaptive sampling patterns and reconstruction; measured BRDFs; and instant global illumination, as well as subsurface and multiple-scattering integrators.These updates reflect the current state-of-the-art technology, and along with the lucid pairing of text and code, ensure the book's leading position as a reference text for those working with images, whether it is for film, video, photography, digital design, visualization, or gaming.

    It's available on almost every OS--if you master the techniques in this book, you'll never need another text editor. Practical Vim shows you 120 vim recipes so you can quickly learn the editor's core functionality and tackle your trickiest editing and writing tasks. Vim, like its classic ancestor vi, is a serious tool for programmers, web developers, and sysadmins. No other text editor comes close to Vim for speed and efficiency; it runs on almost every system imaginable and supports most coding and markup languages. Learn how to edit text the "Vim way:" complete a series of repetitive changes with The Dot Formula, using one keystroke to strike the target, followed by one keystroke to execute the change. Automate complex tasks by recording your keystrokes as a macro. Run the same command on a selection of lines, or a set of files. Discover the "very magic" switch, which makes Vim's regular expression syntax more like Perl's. Build complex patterns by iterating on your search history. Search inside multiple files, then run Vim's substitute command on the result set for a project-wide search and replace. All without installing a single plugin! You'll learn how to navigate text documents as fast as the eye moves--with only a few keystrokes. Jump from a method call to its definition with a single command. Use Vim's jumplist, so that you can always follow the breadcrumb trail back to the file you were working on before. Discover a multilingual spell-checker that does what it's told.Practical Vim will show you new ways to work with Vim more efficiently, whether you're a beginner or an intermediate Vim user. All this, without having to touch the mouse.What You Need: Vim version 7

    As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once.Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs.What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

    It took the open source world by storm since its inception in 2005, and is used by small development shops and giants like Google, Red Hat, and IBM, and of course many open source projects.A book by Git experts to turn you into a Git expert. Introduces the world of distributed version control Shows how to build a Git development workflow.

    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.

    The OpenGL Programming Guide provides definitive and comprehensive information on OpenGL and the OpenGL Utility Library. It is far and away the most important book on OpenGL, and is commonly referred to by programmers simply as the Red book. Last summer the OpenGL Architectural Review Board (ARB) announced the release of the version 2.0 standard, incorporating the OpenGL Shader Language (GLSL) officially into the spec. This is the biggest change in OpenGL since its inception. This new edition will provide basic information about GLSL itself, as well as all the other changes to the 1.5 and 1.0 versions. the official, comprehensive guide to GLSL itself. A few years ago, pundits were predicting the imminent demise of OpenGL. Far from expiring, however, OpenGL has had a resurgence in the last couple years, and has solidified its position as the defacto standard for high-quality computer graphics. This book remains the necessary guide for any developer doing graphics programming. The sample source code in the book will be available on the book's web site.

    Today, twenty million people worldwide are surfing the Net. Where Wizards Stay Up Late is the exciting story of the pioneers responsible for creating the most talked about, most influential, and most far-reaching communications breakthrough since the invention of the telephone. In the 1960's, when computers where regarded as mere giant calculators, J.C.R. Licklider at MIT saw them as the ultimate communications devices. With Defense Department funds, he and a band of visionary computer whizzes began work on a nationwide, interlocking network of computers. Taking readers behind the scenes, Where Wizards Stay Up Late captures the hard work, genius, and happy accidents of their daring, stunningly successful venture.