This book builds on the contributions and strengths of seminal technologies like Spring, Hibernate, and TopLink.EJB 3 is the most important innovation introduced in Java EE 5.0. EJB 3 simplifies enterprise development, abandoning the complex EJB 2.x model in favor of a lightweight POJO framework. The new API represents a fresh perspective on EJB without sacrificing the mission of enabling business application developers to create robust, scalable, standards-based solutions.EJB 3 in Action is a fast-paced tutorial, geared toward helping you learn EJB 3 and the Java Persistence API quickly and easily. For newcomers to EJB, this book provides a solid foundation in EJB. For the developer moving to EJB 3 from EJB 2, this book addresses the changes both in the EJB API and in the way the developer should approach EJB and persistence.

    Completely Revised for the New 2007 Version of the CCNA Exam (#640-802) Cisco networking authority Todd Lammle has completely updated this new edition to cover all of the exam objectives for the latest version of the CCNA exam.

    Along with a clear introduction to asynchronous programming, you get an in-depth look at how the async feature works and why you might want to use it in your application.Written for experienced C# programmers—yet approachable for beginners—this book is packed with code examples that you can extend for your own projects.Write your own asynchronous code, and learn how async saves you from this messy choreDiscover new performance possibilities in ASP.NET web server codeExplore how async and WinRT work together in Windows 8 applicationsLearn the importance of the await keyword in async methodsUnderstand which .NET thread is running your code—and at what points in the programUse the Task-based Asynchronous Pattern (TAP) to write asynchronous APIs in .NETTake advantage of parallel computing in modern machinesMeasure async code performance by comparing it with alternatives

    Today, Rails developers and architects need better ways to interface with legacy systems, move into the cloud, and scale to handle higher volumes and greater complexity. In Service-Oriented Design with Ruby and Rails Paul Dix introduces a powerful, services-based design approach geared toward overcoming all these challenges. Using Dix's techniques, readers can leverage the full benefits of both Ruby and Rails, while overcoming the difficulties of working with larger codebases and teams. Dix demonstrates how to integrate multiple components within an enterprise application stack; create services that can easily grow and connect; and design systems that are easier to maintain and upgrade. Key concepts are explained with detailed Ruby code built using open source libraries such as ActiveRecord, Sinatra, Nokogiri, and Typhoeus. The book concludes with coverage of security, scaling, messaging, and interfacing with third-party services. Service-Oriented Design with Ruby and Rails will help you Build highly scalable, Ruby-based service architectures that operate smoothly in the cloud or with legacy systems Scale Rails systems to handle more requests, larger development teams, and more complex code bases Master new best practices for designing and creating services in Ruby Use Ruby to glue together services written in any language Use Ruby libraries to build and consume RESTful Web services Use Ruby JSON parsers to quickly represent resources from HTTP services Write lightweight, well-designed API wrappers around internal or external services Discover powerful non-Rails frameworks that simplify Ruby service implementation Implement standards-based enterprise messaging with Advanced Message Queuing Protocol (AMQP) Optimize performance with load balancing and caching Provide for security and authentication

    It's aimed at developers who might not be quite comfortable with the idea of pointers and static typing.http://openmymind.net/The-Little-Go-B...

    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.

    Siracusa's overview, wrap-up, and critique of everything new in OS X 10.10 Yosemite.

    A LISP "toolkit" in each chapter explains how to use Common LISP programming and debugging tools such as DESCRIBE, INSPECT, TRACE and STEP.

    Create a tiny virtual environment, called a container, for your application that includes only its particular set of dependencies. The Docker engine accounts for, manages, and builds these containers through functionality provided by the host operating system. Software running inside containers share the Linux OS and other resources, such as libraries, making their footprints radically smaller, and the containerized applications are easy to install, manage, and remove. Developers can package their applications without worrying about environment-specific deployment concerns, and the operations team gets cleaner, more efficient systems across the board. Better still, Docker is free and open source.Docker in Action teaches readers how to create, deploy, and manage applications hosted in Docker containers. The book starts with a clear explanation of the Docker model of virtualization, comparing this approach to the traditional hypervisor model. Developers will learn how to package applications in containers, including specific techniques for testing and distributing applications via Docker Hub and other registries. Readers will learn how to take advantage of the Linux OS features that Docker uses to run programs securely, and how to manage shared resources. Using carefully-designed examples, the book teaches you how to orchestrate containers and applications from installation to removal. Along the way, you'll learn techniques for using Docker on systems ranging from your personal dev-and-test machine to full-scale cloud deployments.

    

    . . . 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.

    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.

    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.

    Like previous versions, this guide shows you step-by-step techniques on using MVC to best advantage, with plenty of practical tutorials to illustrate the concepts. It covers controllers, views, and models; forms and HTML helpers; data annotation and validation; membership, authorization, and security.MVC 5, the latest version of MVC, adds sophisticated features such as single page applications, mobile optimization, and adaptive rendering A team of top Microsoft MVP experts, along with visionaries in the field, provide practical advice on basic and advanced MVC topics Covers controllers, views, models, forms, data annotations, authorization and security, Ajax, routing, ASP.NET web API, dependency injection, unit testing, real-world application, and much more Professional ASP.NET MVC 5 is the comprehensive resource you need to make the best use of the updated Model-View-Controller technology.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.