Getting started with this JavaScript library is easy, but it can take years to fully realize its breadth and depth; this cookbook shortens the learning curve considerably. With these recipes, you'll learn patterns and practices from 19 leading developers who use jQuery for everything from integrating simple components into websites and applications to developing complex, high-performance user interfaces. Ideal for newcomers and JavaScript veterans alike, jQuery Cookbook starts with the basics and then moves to practical use cases with tested solutions to common web development hurdles. You also get recipes on advanced topics, such as methods for applying jQuery to large projects.Solve problems involving events, effects, dimensions, forms, themes, and user interface elementsLearn how to enhance your forms, and how to position and reposition elements on a pageMake the most of jQuery's event management system, including custom events and custom event dataCreate UI elements-such as tabs, accordions, and modals-from scratchOptimize your code to eliminate bottlenecks and ensure peak performanceLearn how to test your jQuery applicationsThe book's contributors include:Cody LindleyJames PadolseyRalph WhitbeckJonathan SharpMichael Geary and Scott GonzálezRebecca MurpheyRemy SharpAriel FleslerBrian CherneJörn ZaeffererMike HostetlerNathan SmithRichard D. WorthMaggie Wachs, Scott Jehl, Todd Parker, and Patty TolandRob Burns

    Designed for readers who don't need the academic formality, it's a fast and easy computer science guide. It teaches essential concepts for people who want to program computers effectively. First, it introduces discrete mathematics, then it exposes the most common algorithms and data structures. It also shows the principles that make computers and programming languages work.

    But if one per year is good, how about Seven Languages in Seven Weeks? In this book you'll get a hands-on tour of Clojure, Haskell, Io, Prolog, Scala, Erlang, and Ruby. Whether or not your favorite language is on that list, you'll broaden your perspective of programming by examining these languages side-by-side. You'll learn something new from each, and best of all, you'll learn how to learn a language quickly. Ruby, Io, Prolog, Scala, Erlang, Clojure, Haskell. With Seven Languages in Seven Weeks, by Bruce A. Tate, you'll go beyond the syntax-and beyond the 20-minute tutorial you'll find someplace online. This book has an audacious goal: to present a meaningful exploration of seven languages within a single book. Rather than serve as a complete reference or installation guide, Seven Languages hits what's essential and unique about each language. Moreover, this approach will help teach you how to grok new languages. For each language, you'll solve a nontrivial problem, using techniques that show off the language's most important features. As the book proceeds, you'll discover the strengths and weaknesses of the languages, while dissecting the process of learning languages quickly--for example, finding the typing and programming models, decision structures, and how you interact with them. Among this group of seven, you'll explore the most critical programming models of our time. Learn the dynamic typing that makes Ruby, Python, and Perl so flexible and compelling. Understand the underlying prototype system that's at the heart of JavaScript. See how pattern matching in Prolog shaped the development of Scala and Erlang. Discover how pure functional programming in Haskell is different from the Lisp family of languages, including Clojure. Explore the concurrency techniques that are quickly becoming the backbone of a new generation of Internet applications. Find out how to use Erlang's let-it-crash philosophy for building fault-tolerant systems. Understand the actor model that drives concurrency design in Io and Scala. Learn how Clojure uses versioning to solve some of the most difficult concurrency problems. It's all here, all in one place. Use the concepts from one language to find creative solutions in another-or discover a language that may become one of your favorites.

    It's the expertise you need when your start-up gets an unexpected spike in web traffic, or when a new feature causes your mature application to fail. In this collection of essays and interviews, web veterans such as Theo Schlossnagle, Baron Schwartz, and Alistair Croll offer insights into this evolving field. You'll learn stories from the trenches--from builders of some of the biggest sites on the Web--on what's necessary to help a site thrive.Learn the skills needed in web operations, and why they're gained through experience rather than schoolingUnderstand why it's important to gather metrics from both your application and infrastructureConsider common approaches to database architectures and the pitfalls that come with increasing scaleLearn how to handle the human side of outages and degradationsFind out how one company avoided disaster after a huge traffic delugeDiscover what went wrong after a problem occurs, and how to prevent it from happening againContributors include:John AllspawHeather ChampMichael ChristianRichard CookAlistair CrollPatrick DeboisEric FlorenzanoPaul HammondJustin HuffAdam JacobJacob LoomisMatt MassieBrian MoonAnoop NagwaniSean PowerEric RiesTheo SchlossnagleBaron SchwartzAndrew Shafer

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

    We'll use the world's most popular functional programming language: JavaScript. Some may feel this is a poor choice as it's against the grain of the current culture which, at the moment, feels predominately imperative. However, I believe it is the best way to learn FP for several reasons:You likely use it every day at work.This makes it possible to practice and apply your acquired knowledge each day on real world programs rather than pet projects on nights and weekends in an esoteric FP language.We don't have to learn everything up front to start writing programs.In a pure functional language, you cannot log a variable or read a DOM node without using monads. Here we can cheat a little as we learn to purify our codebase. It's also easier to get started in this language since it's mixed paradigm and you can fall back on your current practices while there are gaps in your knowledge.The language is fully capable of writing top notch functional code.We have all the features we need to mimic a language like Scala or Haskell with the help of a tiny library or two. Object-oriented programming currently dominates the industry, but it's clearly awkward in JavaScript. It's akin to camping off of a highway or tap dancing in galoshes. We have to bind all over the place lest this change out from under us, we don't have classes[^Yet], we have various work arounds for the quirky behavior when the new keyword is forgotten, private members are only available via closures. To a lot of us, FP feels more natural anyways.That said, typed functional languages will, without a doubt, be the best place to code in the style presented by this book. JavaScript will be our means of learning a paradigm, where you apply it is up to you. Luckily, the interfaces are mathematical and, as such, ubiquitous. You'll find yourself at home with swiftz, scalaz, haskell, purescript, and other mathematically inclined environments.

    As traffic volume and data demands increase, these applications become more complicated and brittle, exposing risks and compromising availability. This practical guide shows IT, devops, and system reliability managers how to prevent an application from becoming slow, inconsistent, or downright unavailable as it grows.Scaling isn't just about handling more users; it's also about managing risk and ensuring availability. Author Lee Atchison provides basic techniques for building applications that can handle huge quantities of traffic, data, and demand without affecting the quality your customers expect.In five parts, this book explores:Availability: learn techniques for building highly available applications, and for tracking and improving availability going forwardRisk management: identify, mitigate, and manage risks in your application, test your recovery/disaster plans, and build out systems that contain fewer risksServices and microservices: understand the value of services for building complicated applications that need to operate at higher scaleScaling applications: assign services to specific teams, label the criticalness of each service, and devise failure scenarios and recovery plansCloud services: understand the structure of cloud-based services, resource allocation, and service distribution

    Not only does this Bible give you a quick refresher on the structure of open-source Linux software, it also shows you how to bypass the hefty graphical user interface on Linux systems and start interacting the fast and efficient way?with command lines and automated scripts. You'll learn how to manage files on the filesystem, start and stop programs, use databases, even do Web programming?without a GUI?with this one-stop resource.

    Elements of programming.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    With "React: Up and Running" you'll learn how to get off the ground with React, with no prior knowledge.This book teaches you how to build components, the building blocks of your apps, as well as how to organize the components into large-scale apps. In addition, you ll learn about unit testing and optimizing performance, while focusing on the application s data (and letting the UI take care of itself)."

    An approachable guide to programming in SQL (Structured Query Language) that will teach even beginning programmers how to build powerful databases and analyze data to find meaningful information.Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language) written by longtime professional journalist Anthony DeBarros. SQL is the primary tool that programmers, web developers, researchers, journalists, and others use to explore data in a database. DeBarros focuses on using SQL to find the story in data, with the aid of the popular open-source database PostgreSQL and the pgAdmin interface.This thoroughly revised second edition includes a new chapter describing how to set up PostgreSQL and more extensive discussion of pgAdmin's best features. The author has also added a chapter on the JSON data format that shows readers how to store and query JSON data. DeBarros has also updated the data in the book throughout, added coverage of additional topics, and perfected the book's examples.Readers love DeBarros's use of exercises and real-world examples that demonstrate how to:- Create databases and related tables using your own data - Correctly define data typesAggregate, sort, and filter data to find patterns - Clean their data and transfer data as text files - Create advanced queries and automate tasksThis book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.

    You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms

    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