In Understanding ECMAScript 6, expert developer Nicholas C. Zakas provides a complete guide to the object types, syntax, and other exciting changes that ECMAScript 6 brings to JavaScript. Every chapter is packed with example code that works in any JavaScript environment so you'll be able to see new features in action. You'll learn:How ECMAScript 6 class syntax relates to more familiar JavaScript conceptsWhat makes iterators and generators usefulHow arrow functions differ from regular functionsWays to store data with sets, maps, and moreThe power of inheritanceHow to improve asynchronous programming with promisesHow modules change the way you organize codeWhether you're a web developer or a Node.js developer, you'll find Understanding ECMAScript 6 indispensable on your journey from ECMAScript 5 to ECMAScript 6.

    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.

    'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

    In addition to giving a strong foundation in the language itself, Lubanovic shows how to use it for a range of applications in business, science, and the arts, drawing on the rich collection of open source packages developed by Python fans.It's impressive how many commercial and production-critical programs are written now in Python. Developed to be easy to read and maintain, it has proven a boon to anyone who wants applications that are quick to write but robust and able to remain in production for the long haul.This book focuses on the current version of Python, 3.x, while including sidebars about important differences with 2.x for readers who may have to deal with programs in that version.

    With our Cookbook's unique format, you can learn how to build dynamic web applications that work on any web browser. This revised new edition makes it easy to find specific solutions for programming challenges.PHP Cookbook has a wealth of solutions for problems that you'll face regularly. With topics that range from beginner questions to advanced web programming techniques, this guide contains practical examples -- or "recipes" -- for anyone who uses this scripting language to generate dynamic web content. Updated for PHP 5, this book provides solutions that explain how to use the new language features in detail, including the vastly improved object-oriented capabilities and the new PDO data access extension. New sections on classes and objects are included, along with new material on processing XML, building web services with PHP, and working with SOAP/REST architectures. With each recipe, the authors include a discussion that explains the logic and concepts underlying the solution.

    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

    R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems.Understand the basics of the language, including the nature of R objectsLearn how to write R functions and build your own packagesWork with data through visualization, statistical analysis, and other methodsExplore the wealth of packages contributed by the R communityBecome familiar with the lattice graphics package for high-level data visualizationLearn about bioinformatics packages provided by Bioconductor"I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."

    It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpayd�n offers a concise and accessible overview of the new AI. This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpayd�n, author of a popular textbook on machine learning, explains that as Big Data has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.

    You’ll learn how each of these platform-agnostic patterns work, when they might be useful in the cloud, and what impact they’ll have on your application architecture. You’ll also see an example of each pattern applied to an application built with Windows Azure.The patterns are organized into four major topics, such as scalability and handling failure, and primer chapters provide background on each topic. With the information in this book, you’ll be able to make informed decisions for designing effective cloud-native applications that maximize the value of cloud services, while also paying attention to user experience and operational efficiency.Learn about architectural patterns for:Scalability. Discover the advantages of horizontal scaling. Patterns covered include Horizontally Scaling Compute, Queue-Centric Workflow, and Auto-Scaling.Big data. Learn how to handle large amounts of data across a distributed system. Eventual consistency is explained, along with the MapReduce and Database Sharding patterns.Handling failure. Understand how multitenant cloud services and commodity hardware influence your applications. Patterns covered include Busy Signal and Node Failure.Distributed users. Learn how to overcome delays due to network latency when building applications for a geographically distributed user base. Patterns covered include Colocation, Valet Key, CDN, and Multi-Site Deployment.

    . ." and "The data bear this out. . . ." But the field of statistics is not just about data. Statistics is the entire process involved in gathering evidence to answer questions about the world, in cases where that evidence happens to be numerical data. Statistics For Dummies is for everyone who wants to sort through and evaluate the incredible amount of statistical information that comes to them on a daily basis. (You know the stuff: charts, graphs, tables, as well as headlines that talk about the results of the latest poll, survey, experiment, or other scientific study.) This book arms you with the ability to decipher and make important decisions about statistical results, being ever aware of the ways in which people can mislead you with statistics. Get the inside scoop on number-crunching nuances, plus insight into how you canDetermine the odds Calculate a standard score Find the margin of error Recognize the impact of polls Establish criteria for a good survey Make informed decisions about experiments This down-to-earth reference is chock-full of real examples from real sources that are relevant to your everyday life: from the latest medical breakthroughs, crime studies, and population trends to surveys on Internet dating, cell phone use, and the worst cars of the millennium. Statistics For Dummies departs from traditional statistics texts, references, supplement books, and study guides in the following ways:Practical and intuitive explanations of statistical concepts, ideas, techniques, formulas, and calculations. Clear and concise step-by-step procedures that intuitively explain how to work through statistics problems. Upfront and honest answers to your questions like, "What does this really mean?" and "When and how I will ever use this?" Chances are, Statistics For Dummies will be your No. 1 resource for discovering how numerical data figures into your corner of the universe.

    In this richly illustrated book, accessible examples are used to show how information theory can be understood in terms of everyday games like '20 Questions', and the simple MatLab programs provided give hands-on experience of information theory in action. Written in a tutorial style, with a comprehensive glossary, this text represents an ideal primer for novices who wish to become familiar with the basic principles of information theory.Download chapter 1 from http://jim-stone.staff.shef.ac.uk/Boo...

    Packed with real-world examples, this book teaches you all the essentials of server-side programming, from the fundamentals of PHP and MySQL coding to advanced topics such as form validation, session IDs, cookies, database queries and joins, file I/O operations, content management, and more.Head First PHP & MySQL offers the same visually rich format that's turned every title in the Head First series into a bestseller, with plenty of exercises, quizzes, puzzles, and other interactive features to help you retain what you've learned.Use PHP to transform static HTML pages into dynamic web sites Create and populate your own MySQL database tables, and work with data stored in files Perform sophisticated MySQL queries with joins, and refine your results with LIMIT and ORDER BY Use cookies and sessions to track visitors' login information and personalize the site for users Protect your data from SQL injection attacks Use regular expressions to validate information on forms Dynamically display text based on session info and create images on the fly Pull syndicated data from other sites using PHP and XML Throughout the book, you'll build sophisticated examples -- including a mailing list, a job board, and an online dating site -- to help you learn how to harness the power of PHP and MySQL in a variety of contexts. If you're ready to build a truly dynamic website, Head First PHP & MySQL is the ideal way to get going.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    Today’s "machine-learning" systems, trained by data, are so effective that we’ve invited them to see and hear for us?and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem.Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole?and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands.The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software.In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story.The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.

    It is designed as a reference for students in the physical sciences and engineering.