"Web Analytics 2.0" presents a new framework that will permanently change how you think about analytics. It provides specific recommendations for creating an actionable strategy, applying analytical techniques correctly, solving challenges such as measuring social media and multichannel campaigns, achieving optimal success by leveraging experimentation, and employing tactics for truly listening to your customers. The book will help your organization become more data driven while you become a super analysis ninja Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

    A good graphic says ‘See what I see!’ and either you do or you don’t. The best ones…pull you right in, and won’t let you go.” —From the introduction by Robert KrulwichThe year’s most “awesome” (RedOrbit) infographics reveal aspects of our world in often startling ways—from a haunting graphic mapping the journey of 15,790 slave ships over 315 years, to a yearlong data drawing project on postcards that records and cements a trans-Atlantic friendship. The Best American Infographics 2016 covers the realms of social issues, health, sports, arts and culture, and politics—including crisp visual data on the likely Democratic/Republican leanings of an array of professions (proving that your urologist is far more likely to be a Republican than your pediatrician). Here once again are the most innovative print and electronic infographics—“the full spectrum of the genre—from authoritative to playful” (Scientific American).   ROBERT KRULWICH is the cohost of Radiolab and a science correspondent for NPR. He writes, draws, and cartoons at Curiously Krulwich, where he synthesizes scientific concepts into colorful, one-of-a-kind blog posts. He has won several Emmy awards for his work on television, and has been called “the most inventive network reporter in television” by TV Guide.

    This book is an introduction to the concepts of computer programming within the context of the visual arts. It offers a comprehensive reference and text for Processing (www.processing.org), an open-source programming language that can be used by students, artists, designers, architects, researchers, and anyone who wants to program images, animation, and interactivity. The ideas in Processing have been tested in classrooms, workshops, and arts institutions, including UCLA, Carnegie Mellon, New York University, and Harvard University. Tutorial units make up the bulk of the book and introduce the syntax and concepts of software (including variables, functions, and object-oriented programming), cover such topics as photography and drawing in relation to software, and feature many short, prototypical example programs with related images and explanations. More advanced professional projects from such domains as animation, performance, and typography are discussed in interviews with their creators. "Extensions" present concise introductions to further areas of investigation, including computer vision, sound, and electronics. Appendixes, references to additional material, and a glossary contain additional technical details. Processing can be used by reading each unit in order, or by following each category from the beginning of the book to the end. The Processing software and all of the code presented can be downloaded and run for future exploration.Includes essays by Alexander R. Galloway, Golan Levin, R. Luke DuBois, Simon Greenwold, Francis Li, and Hernando Barragan and interviews with Jared Tarbell, Martin Wattenberg, James Paterson, Erik van Blockland, Ed Burton, Josh On, Jurg Lehni, Auriea Harvey and Michael Samyn, Mathew Cullen and Grady Hall, Bob Sabiston, Jennifer Steinkamp, Ruth Jarman and Joseph Gerhardt, Sue Costabile, Chris Csikszentmihalyi, Golan Levin and Zachary Lieberman, and Mark Hansen.Casey Reas is Associate Professor in the Design Media Arts Department at the University of California, Los Angeles. Ben Fry is Nierenburg Chair of Design in the School of Design at Carnegie Mellon University, 2006-2007."

    Today, more and more graphic designers, advertising agencies, motion designers, and artists work in this area. New techniques and forms of expression are being developed. Consequently, the demand for information on this topic has grown enormously. Data Flow 2 expands the definition of contemporary information graphics. The book features new possibilities for diagrams, maps, and charts. It investigates the visual and intuitive presentation of processes, data, and information. Concrete examples of research and art projects as well as commercial work illuminate how techniques such as simplification, abstraction, metaphor, and dramatization function. The book also includes interviews with experts such as The New York Times s Steve Duenes, Infosthetics's Andrew Vande Moere, Visualcomplexity's Manuel Lima, ART+COM's Joachim Sauter, and passionate cartographer Menno-Jan Kraak as well as text features by Johannes Schardt about the challenges in creating effective information graphics and about the relationship between complexity, clarity, content, and innovation. Offering practical advice, background information, case studies, and inspiration, Data Flow 2 is a valuable reference for anyone working with or interested in information graphics.

    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

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    Not to worry: This book is the one place you can turn to find quick, non-intimidating, excellent design help. In The Non-Designer's Design Book, 2nd Edition, best-selling author Robin Williams turns her attention to the basic principles of good design and typography. All you have to do is follow her clearly explained concepts, and you'll begin producing more sophisticated, professional, and interesting pages immediately. Humor-infused, jargon-free prose interspersed with design exercises, quizzes, illustrations, and dozens of examples make learning a snap—which is just what audiences have come to expect from this best-selling author.

    This comprehensive guide is intended to advance the progress of designers seeking to deepen their typographic expertise. Typography Essentials is a practical, hands-on resource to distill, organize, and compartmentalize—but not to oversimplify—the many complex issues surrounding the effective use of typography. It is for designers of every medium in which type plays a major role, and is organized and designed to make the process enjoyable and entertaining, as well as instructional.This book is divided into four easy-to-use sections: The Letter, The Word, The Paragraph, and The Page. Each of the 100 principles has an explanation and examples representing the principle in action.

    Diagrams, data and information graphics are utilised wherever increasingly complex elements are present, whether it is in magazines, non-fiction books or business reports, packages or exhibition designs. Data Flow presents an abundant range of possibilities in visualising data and information. Today, diagrams are being applied beyond their classical fields of use. In addition to archetypical diagrams such as pie charts and histograms, there are manifold types of diagrams developed for use in distinct cases and categories. These range from chart-like diagrams such as bar, plot, line diagrams and spider charts, graph-based diagrams including line, matrix, process flow, and molecular diagrams to extremely complex three-dimensional diagrams. The more concrete the variables, the more aesthetically elaborate the graphics ???????????????????????? sometimes reaching the point of art ???????????????????????? the more abstract, the simpler the readability. The abundant examples in Data Flow showcase the various methodologies behind information design with solutions concerning complexity, simplification, readability and the (over)production of information. In addition to the examples shown, the book features explanatory text. On 256 pages, Data Flow introduces a comprehensive selection of innovatively designed diagrams. This up-to-date survey provides inspiration and concrete solutions for designers, and at the same time unlocks a new field of visual codes.

    The story of information begins in a time profoundly unlike our own, when every thought and utterance vanishes as soon as it is born. From the invention of scripts and alphabets to the long-misunderstood talking drums of Africa, Gleick tells the story of information technologies that changed the very nature of human consciousness. He provides portraits of the key figures contributing to the inexorable development of our modern understanding of information: Charles Babbage, the idiosyncratic inventor of the first great mechanical computer; Ada Byron, the brilliant and doomed daughter of the poet, who became the first true programmer; pivotal figures like Samuel Morse and Alan Turing; and Claude Shannon, the creator of information theory itself. And then the information age arrives. Citizens of this world become experts willy-nilly: aficionados of bits and bytes. And we sometimes feel we are drowning, swept by a deluge of signs and signals, news and images, blogs and tweets. The Information is the story of how we got here and where we are heading.

    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.

    The show celebrates design and architecture in all of its functional glory and accidental absurdity, with intriguing tales of both designers and the people impacted by their designs.Now, in The 99% Invisible City: A Field Guide to Hidden World of Everyday Design, host Roman Mars and coauthor Kurt Kohlstedt zoom in on the various elements that make our cities work, exploring the origins and other fascinating stories behind everything from power grids and fire escapes to drinking fountains and street signs. With deeply researched entries and beautiful line drawings throughout, The 99% Invisible City will captivate devoted fans of the show and anyone curious about design, urban environments, and the unsung marvels of the world around them.

     If you have ever found yourself lost halfway through other introductory materials on this topic, this is the book for you. If you don't understand set terminology such as vectors, hyperplanes, and centroids, then this is also the book for you. This starter course isn't a picture story book but does include many visual examples that break algorithms down into a digestible and practical format. As a starter course, this book connects the dots and offers the crash course I wish I had when I first started. The kind of guide I wish had before I started taking on introductory courses that presume you’re two days away from an advanced mathematics exam. That’s why this introductory course doesn’t go further on the subject than other introductory books, but rather, goes a step back. A half-step back in order to help everyone make his or her first strides in machine learning and is an ideal study companion for the visual learner. In this step-by-step guide you will learn: - How to download free datasets - What tools and software packages you need - Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data - Preparing data for analysis, including k-fold Validation - Regression analysis to create trend lines - Clustering, including k-means and k-nearest Neighbors - Naive Bayes Classifier to predict new classes - Anomaly detection and SVM algorithms to combat anomalies and outliers - The basics of Neural Networks - Bias/Variance to improve your machine learning model - Decision Trees to decode classification Please feel welcome to join this starter course by buying a copy, or sending a free sample to your preferred device.

    Infographica collects intriguing data from across our planet - including facial hair styles of famous dictators, the countries with the most McDonald's restaurants and the world's most expensive divorces - and presents it in stylish, memorable and original infographics.