Due to their monopoly position in web browsers, and the fact web browsers have spread from PCs to phones, tablets and TVs; their status will continue to grow and grow. Despite their success, many software engineers are apprehensive about JavaScript and HTML. This apprehensiveness is not completely unfounded; both JavaScript and HTML were rushed in their early years, and driven by commercial rather than engineering interests. As a result, many dubious features crept into these languages. Due to backwards compatibility concerns, most of these features still remain. In addition, many software engineers have used these languages without ever learning them. JavaScript and HTML have low barriers to entry, and this, along with their similarity to other languages, led many software engineers to conclude that there really was nothing much to learn. If you have not used JavaScript and HTML for a number of years, or if you are a programmer or software engineer using other languages, you may be surprised at what they now offer. Browser based web applications are now capable of matching or exceeding the sophistication and scale of traditional desktop applications. In order to create complex web applications however, it is essential to learn these languages. This book takes the point of view that once you have a strong grasp of the fundamentals, the details will take care of themselves. It will not present you with long lists of APIs, or intricate details of every attribute, these can be found in reference manuals. It will focus on the details of each language that are fundamental to understanding how they work. This book will guide you through the process of developing a web application using HTML5, Javascript, jQuery and CSS. It contains the following content: 1. An introduction to the HTML5 markup language, and how it differs from HTML4 and XHTML. 2. An introduction to JavaScript, including an in-depth look at its use of objects and functions, along with the design patterns that support the development of robust web applications. 3. An introduction to jQuery selection, traversal, manipulation and events. 4. An in-depth look at the Web storage and IndexedDB APIs for client side data storage. 5. A guide to implementing offline web applications with the Application Cache API. 6. An introduction to the ways JavaScript can interact with the users file-system using the FileReader API. 7. The use of Web Workers in a web application to execute algorithms on background threads. 8. An introduction to AJAX, and the jQuery API supporting AJAX. 9. An introduction to Server Sent Events and Web Sockets. All subjects are introduced in the context of a sample web application. This book is intended for anyone with at least a superficial knowledge of HTML and programming.

    The twelve-factor app is a methodology for building software-as-a-service apps that: - Use declarative formats for setup automation, to minimize time and cost for new developers joining the project; - Have a clean contract with the underlying operating system, offering maximum portability between execution environments; - Are suitable for deployment on modern cloud platforms, obviating the need for servers and systems administration; - Minimize divergence between development and production, enabling continuous deployment for maximum agility; - And can scale up without significant changes to tooling, architecture, or development practices.The twelve-factor methodology can be applied to apps written in any programming language, and which use any combination of backing services (database, queue, memory cache, etc).

    Hundreds of thousands of pianos are bought and sold each year, yet most people buy a piano with only the vaguest idea of what to look for as they make this major purchase. The Piano Book evaluates and compares every brand and style of piano sold in the United States. There is information on piano moving and storage, inspecting individual new and used pianos, the special market for Steinways, and sales gimmicks to watch out for. An annual supplement, sold separately, lists current prices for more than 2,500 new piano models.

    Big Blue, as the company is known, tends to rely for its success on magical thinking but that magic ran out a long time ago. The company got in trouble back in the 1990s and had to hire for the first time an outside CEO, Lou Gerstner, to save the day. Gerstner pushed IBM into services with spectacular results but this hurt the company, too. As services have became commoditized IBM could only compete by offshoring the work and quality suffered. The other negative impact of Gerstner was his compensation which was for the first time in IBM history very high. Only the Watson family had become rich running IBM with later CEOs like John Opel and John Akers living comfortable lives with lots of perks, but they never got BIG RICH. That changed with Gerstner. Sam Palmisano an IBM lifer followed Gerstner as CEO and followed, too, the Gerstner playbook. Palmisano retired three years ago with a retirement package worth $241 million, replaced by IBM's first woman CEO, Ginni Rometty, who certainly expects a comparable golden parachute. In order to achieve these numbers, though, IBM has essentially sacrificed both its customers and employees. In order to have ever growing earnings per share the company has cut labor to the bone, off-shored everything it can, dropped quality, deliberately underbid contracts to win them then not performed. IBM's acquisition policy is one of buying companies to get their sales then cutting costs to the bone and under-delivering. This and share buybacks have kept earnings growing until this house of cards recently began to fall. Ginni Rometty, who will end up taking the fall for Palmisano's flawed strategy, has stated a very specific earnings goal for 2015 that she will destroy the company to achieve if she must. This book how IBM fell from grace, where it is headed, and what specifically can be done to save the company before it is too late.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    While it's safe to say that relational databases aren't going anywhere, we can also say that the ecosystem around data is never going to be the same.Of all the new tools and solutions, for me, Redis has been the most exciting. Why? First because it's unbelievably easy to learn. Hours is the right unit to use when talking about length of time it takes to get comfortable with Redis. Secondly, it solves a specific set of problems while at the same time being quite generic. What exactly does that mean? Redis doesn't try to be all things to all data. As you get to know Redis, it'll become increasingly evident what does and what does not belong in it. And when it does, as a developer, it's a great experience.While you can build a complete system using Redis only, I think most people will find that it supplements their more generic data solution - whether that be a traditional relational database, a document-oriented system, or something else. It's the kind of solution you use to implement specific features. In that way, it's similar to an indexing engine. You wouldn't build your entire application on Lucene. But when you need good search, it's a much better experience - for both you and your users. Of course, the similarities between Redis and indexing engines end there.The goal of this book is to build the foundation you'll need to master Redis. We'll focus on learning Redis' five data structures and look at various data modeling approaches. We'll also touch on some key administrative details and debugging techniques.LicenseThe Little Redis Book is licensed under the Attribution-NonCommercial 3.0 Unported license. You should not have paid for this book.You are free to copy, distribute, modify or display the book. However, I ask that you always attribute the book to me, Karl Seguin, and do not use it for commercial purposes.You can see the full text of the license at:http://creativecommons.org/licenses/b...About The AuthorKarl Seguin is a developer with experience across various fields and technologies. He's an active contributor to Open-Source Software projects, a technical writer and an occasional speaker. He's written various articles, as well as a few tools, about Redis. Redis powers the ranking and statistics of his free service for casual game developers: mogade.com.Karl wrote The Little MongoDB Book, the free and popular book about MongoDB.His blog can be found at http://openmymind.net and he tweets via @karlseguinWith Thanks ToA special thanks to Perry Neal for lending me his eyes, mind and passion. You provided me with invaluable help. Thank you.Latest VersionThe latest source of this book is available at: http://github.com/karlseguin/the-litt...

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    The authors also include examples covering a variety of different integration technologies, such as JMS, MSMQ, TIBCO ActiveEnterprise, Microsoft BizTalk, SOAP, and XSL. A case study describing a bond trading system illustrates the patterns in practice, and the book offers a look at emerging standards, as well as insights into what the future of enterprise integration might hold. This book provides a consistent vocabulary and visual notation framework to describe large-scale integration solutions across many technologies. It also explores in detail the advantages and limitations of asynchronous messaging architectures. The authors present practical advice on designing code that connects an application to a messaging system, and provide extensive information to help you determine when to send a message, how to route it to the proper destination, and how to monitor the health of a messaging system. If you want to know how to manage, monitor, and maintain a messaging system once it is in use, get this book.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    It provides all of JavaScript's functionality wrapped in a cleaner, more succinct syntax. In the first book on this exciting new language, CoffeeScript guru Trevor Burnham shows you how to hold onto all the power and flexibility of JavaScript while writing clearer, cleaner, and safer code.CoffeeScript: Accelerated JavaScript Development offers a thorough introduction to this new language, starting from the basics. You'll learn to use time-saving features like list comprehensions and splats, organize your code into modules with extensible classes, and deploy your work to multiple environments. Each chapter is example-driven and includes challenging exercises to push your CoffeeScript know-how further. Through the course of the book, you'll build a fast-paced multiplayer word game-writing both the client (with jQuery) and server (with Node.js) in CoffeeScript. And because the two languages are so deeply intertwined, you'll deepen your understanding of JavaScript along the way. CoffeeScript makes it easier than ever to write powerful, standards-compliant JavaScript code. CoffeeScript: Accelerated JavaScript Development lets you start doing it today.

    This bestseller talks to readers at their level, explaining every aspect of how to get started and learn the C language quickly. Readers also find out where to learn more about C. This book includes tear-out reference card of C functions and statements, a hierarchy chart, and other valuable information. It uses special icons, notes, clues, warnings, and rewards to make understanding easier. And the clear and friendly style presumes no programming knowledge.

    Mike Loukides kicked things off in June 2010 with “What is data science?” and from there we’ve pursued the various threads and themes that naturally emerged. Now, roughly a year later, we can look back over all we’ve covered and identify a number of core data areas: Data issues -- The opportunities and ambiguities of the data space are evident in discussions around privacy, the implications of data-centric industries, and the debate about the phrase “data science” itself. The application of data: products and processes – A “data product” can emerge from virtually any domain, including everything from data startups to established enterprises to media/journalism to education and research. Data science and data tools -- The tools and technologies that drive data science are of course essential to this space, but the varied techniques being applied are also key to understanding the big data arena.The business of data – Take a closer look at the actions connected to data -- the finding, organizing, and analyzing that provide organizations of all sizes with the information they need to compete.

    In the tradition of The Long Tail, The Age of the Platform demonstrates how the world of business today is vastly different from that of even 10 years ago.

    

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!