It illustrates little-known features and techniques for getting the most from the Tableau toolset, supporting the needs of the business analysts who use the product as well as the data and IT managers who support it.This comprehensive guide covers the core feature set for data analytics, illustrating best practices for creating and sharing specific types of dynamic data visualizations. Featuring a helpful full-color layout, the book covers analyzing data with Tableau Desktop, sharing information with Tableau Server, understanding Tableau functions and calculations, and Use Cases for Tableau Software.Includes little-known, as well as more advanced features and techniques, using detailed, real-world case studies that the author has developed as part of his consulting and training practice Explains why and how Tableau differs from traditional business information analysis tools Shows you how to deploy dashboards and visualizations throughout the enterprise Provides a detailed reference resource that is aimed at users of all skill levels Depicts ways to leverage Tableau across the value chain in the enterprise through case studies that target common business requirements Endorsed by Tableau Software Tableau Your Data shows you how to build dynamic, best-of-breed visualizations using the Tableau Software toolset.

    It’s easy and fun with this practical, hands-on introduction. Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser. Along the way, you’ll expand your web programming skills, using tools such as HTML and JavaScript.This step-by-step guide is ideal whether you’re a designer or visual artist with no programming experience, a reporter exploring the new frontier of data journalism, or anyone who wants to visualize and share data.Learn HTML, CSS, JavaScript, and SVG basicsDynamically generate web page elements from your data—and choose visual encoding rules to style themCreate bar charts, scatter plots, pie charts, stacked bar charts, and force-directed layoutsUse smooth, animated transitions to show changes in your dataIntroduce interactivity to help users explore data through different viewsCreate customized geographic maps with dataExplore hands-on with downloadable code and over 100 examples

    Starting with basic examples, this book is focused solely on Java 8 language changes and related API changes, so you don’t need to buy and read a 900 page book in order to brush up. Lambdas make a programmer's job easier, and this book will teach you how. Coverage includes introductory syntax for lambda expressions, method references that allow you to reuse existing named methods from your codebase, and the collection library in Java 8.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships.If you're a newcomer to both search and distributed systems, you'll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you'll follow a problem-based approach to learn why, when, and how to use Elasticsearch features.Understand how Elasticsearch interprets data in your documentsIndex and query your data to take advantage of search concepts such as relevance and word proximityHandle human language through the effective use of analyzers and queriesSummarize and group data to show overall trends, with aggregations and analyticsUse geo-points and geo-shapes--Elasticsearch's approaches to geolocationModel your data to take advantage of Elasticsearch's horizontal scalabilityLearn how to configure and monitor your cluster in production

    With this hands-on reference, you'll focus on implementation rather than theory, and discover why the RESTful method is far better than technologies like CORBA and SOAP. It's easy to get started with services based on the REST architecture. RESTful Java with JAX-RS includes a technical guide that explains REST and JAX-RS, how they work, and when to use them. With the RESTEasy workbook that follows, you get step-by-step instructions for installing, configuring, and running several working JAX-RS examples using the JBoss RESTEasy implementation of JAX-RS.Work on the design of a distributed RESTful interface, and develop it in Java as a JAX-RS serviceDispatch HTTP requests in JAX-RS, and learn how to extract information from themDeploy your web services within Java Enterprise Edition using the Application class, Default Component Model, EJB Integration, Spring Integration, and JPADiscover several options for securing your web servicesLearn how to implement RESTful design patterns using JAX-RSWrite RESTful clients in Java using libraries and frameworks such as java.net.URL, Apache HTTP Client, and RESTEasy Proxy

    Scripting is a way to harness and customize the power of any Unix system, and it's an essential skill for any Unix users, including system administrators and professional OS X developers. But beneath this simple promise lies a treacherous ocean of variations in Unix commands and standards.bash Cookbook teaches shell scripting the way Unix masters practice the craft. It presents a variety of recipes and tricks for all levels of shell programmers so that anyone can become a proficient user of the most common Unix shell -- the bash shell -- and cygwin or other popular Unix emulation packages. Packed full of useful scripts, along with examples that explain how to create better scripts, this new cookbook gives professionals and power users everything they need to automate routine tasks and enable them to truly manage their systems -- rather than have their systems manage them.

    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.

    Think of the familiar map of the New York City subway system, or a diagram of the human brain. Successful visualizations are beautiful not only for their aesthetic design, but also for elegant layers of detail that efficiently generate insight and new understanding.This book examines the methods of two dozen visualization experts who approach their projects from a variety of perspectives -- as artists, designers, commentators, scientists, analysts, statisticians, and more. Together they demonstrate how visualization can help us make sense of the world.Explore the importance of storytelling with a simple visualization exerciseLearn how color conveys information that our brains recognize before we're fully aware of itDiscover how the books we buy and the people we associate with reveal clues to our deeper selvesRecognize a method to the madness of air travel with a visualization of civilian air trafficFind out how researchers investigate unknown phenomena, from initial sketches to published papers Contributors include:Nick Bilton, Michael E. Driscoll, Jonathan Feinberg, Danyel Fisher, Jessica Hagy, Gregor Hochmuth, Todd Holloway, Noah Iliinsky, Eddie Jabbour, Valdean Klump, Aaron Koblin, Robert Kosara, Valdis Krebs, JoAnn Kuchera-Morin et al., Andrew Odewahn, Adam Perer, Anders Persson, Maximilian Schich, Matthias Shapiro, Julie Steele, Moritz Stefaner, Jer Thorp, Fernanda Viegas, Martin Wattenberg, and Michael Young.

    Mitnick claims that this socialengineering tactic was the single-most effective method in hisarsenal. This indispensable book examines a variety of maneuversthat are aimed at deceiving unsuspecting victims, while it alsoaddresses ways to prevent social engineering threats.Examines social engineering, the science of influencing atarget to perform a desired task or divulge informationArms you with invaluable information about the many methods oftrickery that hackers use in order to gather information with theintent of executing identity theft, fraud, or gaining computersystem accessReveals vital steps for preventing social engineeringthreatsSocial Engineering: The Art of Human Hacking does itspart to prepare you against nefarious hackers--now you can doyour part by putting to good use the critical information withinits pages.

    Using a downloadable programming environment developed by the author, Visualizing Data demonstrates methods for representing data accurately on the Web and elsewhere, complete with user interaction, animation, and more. How do the 3.1 billion A, C, G and T letters of the human genome compare to those of a chimp or a mouse? What do the paths that millions of visitors take through a web site look like? With Visualizing Data, you learn how to answer complex questions like these with thoroughly interactive displays. We're not talking about cookie-cutter charts and graphs. This book teaches you how to design entire interfaces around large, complex data sets with the help of a powerful new design and prototyping tool called "Processing". Used by many researchers and companies to convey specific data in a clear and understandable manner, the Processing beta is available free. With this tool and Visualizing Data as a guide, you'll learn basic visualization principles, how to choose the right kind of display for your purposes, and how to provide interactive features that will bring users to your site over and over. This book teaches you:The seven stages of visualizing data -- acquire, parse, filter, mine, represent, refine, and interact How all data problems begin with a question and end with a narrative construct that provides a clear answer without extraneous details Several example projects with the code to make them work Positive and negative points of each representation discussed. The focus is on customization so that each one best suits what you want to convey about your data set The book does not provide ready-made "visualizations" that can be plugged into any data set. Instead, with chapters divided by types of data rather than types of display, you'll learn how each visualization conveys the unique properties of the data it represents -- why the data was collected, what's interesting about it, and what stories it can tell. Visualizing Data teaches you how to answer questions, not simply display information.

    With the right tools, we can start to make sense of all this data to see patterns and trends that would otherwise be invisible to us. By transforming numbers into graphical shapes, we allow readers to understand the stories those numbers hide. In this practical introduction to understanding and using information graphics, you'll learn how to use data visualizations as tools to see beyond lists of numbers and variables and achieve new insights into the complex world around us. Regardless of the kind of data you're working with-business, science, politics, sports, or even your own personal finances-this book will show you how to use statistical charts, maps, and explanation diagrams to spot the stories in the data and learn new things from it.You'll also get to peek into the creative process of some of the world's most talented designers and visual journalists, including Conde Nast Traveler's John Grimwade, National Geographic Magazine's Fernando Baptista, The New York Times' Steve Duenes, The Washington Post's Hannah Fairfield, Hans Rosling of the Gapminder Foundation, Stanford's Geoff McGhee, and European superstars Moritz Stefaner, Jan Willem Tulp, Stefanie Posavec, and Gregor Aisch. The book also includes a DVD-ROM containing over 90 minutes of video lessons that expand on core concepts explained within the book and includes even more inspirational information graphics from the world's leading designers.The first book to offer a broad, hands-on introduction to information graphics and visualization, The Functional Art reveals:- Why data visualization should be thought of as "functional art" rather than fine art - How to use color, type, and other graphic tools to make your information graphics more effective, not just better looking - The science of how our brains perceive and remember information - Best practices for creating interactive information graphics - A comprehensive look at the creative process behind successful information graphics - An extensive gallery of inspirational work from the world's top designers and visual artistsOn the DVD-ROM: In this introductory video course on information graphics, Alberto Cairo goes into greater detail with even more visual examples of how to create effective information graphics that function as practical tools for aiding perception. You'll learn how to: incorporate basic design principles in your visualizations, create simple interfaces for interactive graphics, and choose the appropriate type of graphic forms for your data. Cairo also deconstructs successful information graphics from The New York Times and National Geographic magazine with sketches and images not shown in the book.

    With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples.

    It took the open source world by storm since its inception in 2005, and is used by small development shops and giants like Google, Red Hat, and IBM, and of course many open source projects.A book by Git experts to turn you into a Git expert. Introduces the world of distributed version control Shows how to build a Git development workflow.

    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.