"Peter Cooper, Editor of" Ruby Inside Using Rails, developers can build web applications of exceptional elegance and power. Although its remarkable capabilities have made Ruby on Rails one of the world s most popular web development frameworks, it can be challenging to learn and use. " Ruby on Rails Tutorial, Second Edition, " is the solution. Best-selling author and leading Rails developer Michael Hartl teaches Rails by guiding you through the development of your own complete sample application using the latest techniques in Rails web development. The updates to this edition include all-new site design using Twitter s Bootstrap; coverage of the new asset pipeline, including Sprockets and Sass; behavior-driven development (BDD) with Capybara and RSpec; better automated testing with Guard and Spork; roll your own authentication with has_secure_password; and an introduction to Gherkin and Cucumber. You ll find integrated tutorials not only for Rails, but also for the essential Ruby, HTML, CSS, JavaScript, and SQL skills you ll need when developing web applications. Hartl explains how each new technique solves a real-world problem, and he demonstrates this with bite-sized code that s simple enough to understand, yet novel enough to be useful. Whatever your previous web development experience, this book will guide you to true Rails mastery. This book will help you Install and set up your Rails development environment Go beyond generated code to truly understand how to build Rails applications from scratch Learn test-driven development (TDD) with RSpec Effectively use the Model-View-Controller (MVC) pattern Structure applications using the REST architecture Build static pages and transform them into dynamic ones Master the Ruby programming skills all Rails developers need Define high-quality site layouts and data models Implement registration and authentication systems, including validation and secure passwords Update, display, and delete users Add social features and microblogging, including an introduction to Ajax Record version changes with Git and share code at GitHub Simplify application deployment with Heroku

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    In fact, EJB 3.0 is being hailed as the new standard of server-side business logic programming. And O'Reilly's award-winning book on EJB has been refreshed just in time to capitalize on the technology's latest rise in popularity.This fifth edition, written by Bill Burke and Richard Monson-Haefel, has been updated to capture the very latest need-to-know Java technologies in the same award-winning fashion that drove the success of the previous four strong-selling editions. Bill Burke, Chief Architect at JBoss, Inc., represents the company on the EJB 3.0 and Java EE 5 specification committees. Richard Monson-Haefel is one of the world's leading experts on Enterprise Java."Enterprise JavaBeans 3.0," 5th Edition is organized into two parts: the technical manuscript followed by the JBoss workbook. The technical manuscript explains what EJB is, how it works, and when to use it. The JBoss workbook provides step-by-step instructions for installing, configuring, and running the examples from the manuscript on the JBoss 4.0 Application Server.Although EJB makes application development much simpler, it's still a complex and ambitious technology that requires a great deal of time to study and master. But now, thanks to "Enterprise JavaBeans 3.0," 5th Edition, you can overcome the complexities of EJBs and learn from hundreds of practical examples that are largeenough to test key concepts but small enough to be taken apart and explained in the detail that you need. Now you can harness the complexity of EJB with just a single resource by your side.

    The Web is awash in Ruby code that is now virtually impossible to change or extend. This text helps you solve that problem by using powerful real-world object-oriented design techniques, which it thoroughly explains using simple and practical Ruby examples. Sandi Metz has distilled a lifetime of conversations and presentations about object-oriented design into a set of Ruby-focused practices for crafting manageable, extensible, and pleasing code. She shows you how to build new applications that can survive success and repair existing applications that have become impossible to change. Each technique is illustrated with extended examples, all downloadable from the companion Web site, poodr.info. The first title to focus squarely on object-oriented Ruby application design, Practical Object-Oriented Design in Ruby will guide you to superior outcomes, whatever your previous Ruby experience. Novice Ruby programmers will find specific rules to live by; intermediate Ruby programmers will find valuable principles they can flexibly interpret and apply; and advanced Ruby programmers will find a common language they can use to lead development and guide their colleagues. This guide will help you Understand how object-oriented programming can help you craft Ruby code that is easier to maintain and upgrade Decide what belongs in a single Ruby class Avoid entangling objects that should be kept separate Define flexible interfaces among objects Reduce programming overhead costs with duck typing Successfully apply inheritance Build objects via composition Design cost-effective tests Solve common problems associated with poorly designed Ruby code

    This book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, more. Includes exercises. 1976 edition.

    If you're a business or IT professional, this short hands-on guide teaches you how to pull and transform data with SQL in significant ways. You will quickly master the fundamentals of SQL and learn how to create your own databases.Author Thomas Nield provides exercises throughout the book to help you practice your newfound SQL skills at home, without having to use a database server environment. Not only will you learn how to use key SQL statements to find and manipulate your data, but you'll also discover how to efficiently design and manage databases to meet your needs.You'll also learn how to:Explore relational databases, including lightweight and centralized modelsUse SQLite and SQLiteStudio to create lightweight databases in minutesQuery and transform data in meaningful ways by using SELECT, WHERE, GROUP BY, and ORDER BYJoin tables to get a more complete view of your business dataBuild your own tables and centralized databases by using normalized design principlesManage data by learning how to INSERT, DELETE, and UPDATE records

    I've spent the last couple years actively teaching Haskell online and in person. Along the way, I started keeping notes on exercises and methods of teaching specific concepts and techniques in Haskell that eventually turned into my guide for learning haskell. That experience led me to work on this book.If you are new to programming entirely, Haskell is a great first language. You may have noticed the trend of "Functional Programming in [Imperative Language]" books and tutorials and learning Haskell gets right to the heart of what functional programming is. Languages such as Java are gradually adopting functional concepts, but most such languages were not designed to be functional languages, after all. We would not encourage you to learn Haskell as an only language, but because Haskell is a pure functional language, it is a fertile environment for mastering functional programming techniques. That way of thinking and problem solving is useful, no matter what other languages you might know or learn.Haskell is not a difficult language to use. Quite the opposite. I'm now able to tackle problems that I couldn't have tackled when I was primarily a Clojure, Common Lisp, or Python user. Haskell is difficult to teach effectively.

    See the website for links to the C++ and Java version.Have you ever...Wanted to work at an exciting futuristic company?Struggled with an interview problem thatcould have been solved in 15 minutes?Wished you could study real-world computing problems?If so, you need to read Elements of Programming Interviews (EPI).EPI is your comprehensive guide to interviewing for software development roles.The core of EPI is a collection of over 250 problems with detailed solutions. The problems are representative of interview questions asked at leading software companies. The problems are illustrated with 200 figures, 300 tested programs, and 150 additional variants.The book begins with a summary of the nontechnical aspects of interviewing, such as strategies for a great interview, common mistakes, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI. We also provide a summary of data structures, algorithms, and problem solving patterns.Coding problems are presented through a series of chapters on basic and advanced data structures, searching, sorting, algorithm design principles, and concurrency. Each chapter stars with a brief introduction, a case study, top tips, and a review of the most important library methods. This is followed by a broad and thought-provoking set of problems.A practical, fun approach to computer science fundamentals, as seen through the lens of common programming interview questions. Jeff Atwood/Co-founder, Stack Overflow and Discourse

    In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God.Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.

    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!

    At $29 and cheaper than a good pizza, you will get the book in its current partial form, along with all future chapters, updates, and fixes for free. As of the day I wrote this description, Code Bright had 130 pages and was just getting started. To give you some perspective on how detailed it is, Code Happy was 127 pages in its complete state. Want to know more? Carry on reading.Welcome back to Laravel. Last year I wrote a book about the Laravel PHP framework. It started as a collection of tutorials on my blog, and eventually became a full book. I definitely didn’t expect it to be as popular as it was. Code Happy has sold almost 3000 copies, and is considered to be one of the most valuable resourcesfor learning the Laravel framework.Code Bright is the spiritual successor to Code Happy. The framework has grown a lot in the past year, and has changed enough to merit a new title. With Code Bright I hope to improve on Code Happy with every way, my goal is, to once again, build the most comprehensive learning experience for the framework. Oh, and to still be funny. That’s very important to me.Laravel Code Bright will contain a complete learning experience for all of the framework’s features. The style of writing will make it approachable for beginners, and a wonderful reference resource for experienced developers alike.You see, people have told me that they enjoyed reading Code Happy, not only for its educational content, but for its humour, and for my down to earth writing style. This is very important to me. I like to write my books as if we were having a conversation in a bar.When I wrote Code Happy last year, I was simply a framework enthusiast. One of the first to share information about the framework. However, since then I have become a committed member of the core development team. Working directly with the framework author to make Laravel a wonderful experience for the developers of the world.One other important feature of both books, is that they are published while in progress. This means that the book is available in an incomplete state, but will grow over time into a complete title. All future updates will be provided for free.What this means is that I don’t have to worry about deadlines, or a fixed point of completion. It leads to less stress and better writing. If I think of a better way to explain something, I can go back and change it. In a sense, the book will never be completed. I can constantly add more information to it, until it becomes the perfect resource.Given that this time I am using the majority of my spare time to write the title (yes, I have a full time job too!), I have raised the price a little to justify my invested time. I was told by many of my past readers that they found the previous title very cheap for the resource that it grew into, so if you are worried about the new price, then let me remind you what you will get for your 29 bucks.The successor to Code Happy, seen by many as the #1 learning resource for the Laravel PHP framework.An unending source of information, chapters will be constantly added as needed until the book becomes a giant vault of framework knowledge.Comedy, and a little cheesy, but very friendly writing.

    You could spend years discovering solutions to them all, step by step as you encounter them. Or you can just look in here. All successful database applications are destined to eventually run into issues scaling up their performance. Peek into the future of your PostgreSQL database's problems today. Know the warning signs to look for, and how to avoid the most common issues before they even happen. Surprisingly, most PostgreSQL database applications evolve in the same way: Choose the right hardware. Tune the operating system and server memory use. Optimize queries against the database, with the right indexes. Monitor every layer, from hardware to queries, using some tools that are inside PostgreSQL and others that are external. Using monitoring insight, continuously rework the design and configuration. On reaching the limits of a single server, break things up; connection pooling, caching, partitioning, and replication can all help handle increasing database workloads. The path to a high performance database system isn't always easy. But it doesn't have to be mysterious with the right guide. This book is a clear, step-by-step guide to optimizing and scaling up PostgreSQL database servers. - Publisher.