Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    This easy-to-read guide helps you cultivate a host of good development practices, based on classic software design patterns and new patterns unique to embedded programming. Learn how to build system architecture for processors, not operating systems, and discover specific techniques for dealing with hardware difficulties and manufacturing requirements.Written by an expert who’s created embedded systems ranging from urban surveillance and DNA scanners to children’s toys, this book is ideal for intermediate and experienced programmers, no matter what platform you use.Optimize your system to reduce cost and increase performanceDevelop an architecture that makes your software robust in resource-constrained environmentsExplore sensors, motors, and other I/O devicesDo more with less: reduce RAM consumption, code space, processor cycles, and power consumptionLearn how to update embedded code directly in the processorDiscover how to implement complex mathematics on small processorsUnderstand what interviewers look for when you apply for an embedded systems job"Making Embedded Systems is the book for a C programmer who wants to enter the fun (and lucrative) world of embedded systems. It’s very well written—entertaining, even—and filled with clear illustrations." —Jack Ganssle, author and embedded system expert.

    The book progresses into a discussion of the Xbox security mechanisms and other advanced hacking topics, with an emphasis on educating the readers on the important subjects of computer security and reverse engineering. Hacking the Xbox includes numerous practical guides, such as where to get hacking gear, soldering techniques, debugging tips and an Xbox hardware reference guide.Hacking the Xbox also confronts the social and political issues facing today's hacker by looking forward and discussing the impact of today's legal challenges on legitimate reverse engineering activities. The book includes a chapter written by the Electronic Frontier Foundation (EFF) about the rights and responsibilities of hackers, and concludes by discussing the latest trends and vulnerabilities in secure PC platforms.

    It shows teachers how to create an environment in which technology can effectively enhance learning. It contains a technology integration framework that builds on research and the TIP model.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    It is the definitive reference guide, now in a second edition. Although the first edition was written in 1978, it continues to be a worldwide best-seller. This second edition brings the classic original up to date to include the ANSI standard. From the Preface: We have tried to retain the brevity of the first edition. C is not a big language, and it is not well served by a big book. We have improved the exposition of critical features, such as pointers, that are central to C programming. We have refined the original examples, and have added new examples in several chapters. For instance, the treatment of complicated declarations is augmented by programs that convert declarations into words and vice versa. As before, all examples have been tested directly from the text, which is in machine-readable form. As we said in the first preface to the first edition, C "wears well as one's experience with it grows." With a decade more experience, we still feel that way. We hope that this book will help you to learn C and use it well.

    The 20 stand-alone chapters of this new work describe how technological failures result from the incompatibilities between the way things are designed and the way people actually perceive, think, and act. New technologies will succeed or fail based on our ability to minimize these incompatibilities between the characteristics of people and the characteristics of the things we create and use.This book is the quintessential 'must read' for all those who deal with technology in any fashion. From the frustration of an awkward ATM machine to the threat of accidental, nuclear Armageddon, Casey shows how the same crucial factors come into play told through the very eyes of those people who saw and experienced these things. No student of design, psychology, behavioral science, or technology should be without this book, and neither should any intelligent member of society who wants to know what goes on with the successes and failures of modern technology.Sit ringside to the action where compelling events unfold. The stories in this book will take you to airports and airline cabins, an amusement park, a fertility clinic, a pharmaceutical plant, an emergency dispatch center, the Olympic games, and a bank; to hospitals, spacecraft, ships, and cars. From the coasts of Peru and Monterey, in orbit aboard the International Space Station, the freeways of Southern California and the back roads of France, the battlefields of Afghanistan, and a nuclear fuel plant in Japan this is The Atomic Chef.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Based on B. P. Lathi's widely used book, Linear Systems and Signals, it features additional applications to communications, controls, and filtering as well as new chapters on analog and digital filters and digital signal processing. Lathi emphasizes the physical appreciation of concepts rather than the mere mathematical manipulation of symbols. Avoiding the tendency to treat engineering as a branch of applied mathematics, he uses mathematics to enhance physical and intuitive understanding of concepts, instead of employing it only to prove axiomatic theory. Theoretical results are supported by carefully chosen examples and analogies, allowing students to intuitively discover meaning for themselves.

    Now, physicist Leonard Susskind has teamed up with data engineer Art Friedman to present the theory and associated mathematics of the strange world of quantum mechanics.In this follow-up to The Theoretical Minimum, Susskind and Friedman provide a lively introduction to this famously difficult field, which attempts to understand the behavior of sub-atomic objects through mathematical abstractions. Unlike other popularizations that shy away from quantum mechanics’ weirdness, Quantum Mechanics embraces the utter strangeness of quantum logic. The authors offer crystal-clear explanations of the principles of quantum states, uncertainty and time dependence, entanglement, and particle and wave states, among other topics, and each chapter includes exercises to ensure mastery of each area. Like The Theoretical Minimum, this volume runs parallel to Susskind’s eponymous Stanford University-hosted continuing education course.An approachable yet rigorous introduction to a famously difficult topic, Quantum Mechanics provides a tool kit for amateur scientists to learn physics at their own pace.

    Thomas Wolfe wrote standing up in the kitchen, the top of the refrigerator as his desk, dreamily fondling his “male configurations”. . . Jean-Paul Sartre chewed on Corydrane tablets (a mix of amphetamine and aspirin), ingesting ten times the recommended dose each day . . . Descartes liked to linger in bed, his mind wandering in sleep through woods, gardens, and enchanted palaces where he experienced “every pleasure imaginable.” Here are: Anthony Trollope, who demanded of himself that each morning he write three thousand words (250 words every fifteen minutes for three hours) before going off to his job at the postal service, which he kept for thirty-three years during the writing of more than two dozen books . . . Karl Marx . . . Woody Allen . . . Agatha Christie . . . George Balanchine, who did most of his work while ironing . . . Leo Tolstoy . . . Charles Dickens . . . Pablo Picasso . . . George Gershwin, who, said his brother Ira, worked for twelve hours a day from late morning to midnight, composing at the piano in pajamas, bathrobe, and slippers . . . Here also are the daily rituals of Charles Darwin, Andy Warhol, John Updike, Twyla Tharp, Benjamin Franklin, William Faulkner, Jane Austen, Anne Rice, and Igor Stravinsky (he was never able to compose unless he was sure no one could hear him and, when blocked, stood on his head to “clear the brain”). Brilliantly compiled and edited, and filled with detail and anecdote, Daily Rituals is irresistible, addictive, magically inspiring.

    Building on the successful top-down approach of previous editions, this fourth edition continues with an early emphasis on application-layer paradigms and application programming interfaces, encouraging a hands-on experience with protocols and networking concepts.

    Songwriters will examine 17 extraordinary songs and learn the distinct elements that make them so effective. Pattison then presents more than 30 lyric-writing exercises designed to achieve the same results. From generating lyric ideas and managing repetition to developing verses, it's all here. Songwriters will: find warm-up exercises that revolutionize songwriting imagery; use a rhyming dictionary and a thesaurus to generate ideas and find snappy rhyme; create meaningful metaphors and similes while avoiding cliches; develop verses by using or breaking conventional rules; experiment with point of view in every lyric to make a song stand out

    This book attempts to capture the engineering wisdom and design philosophy of the UNIX, Linux, and Open Source software development community as it has evolved over the past three decades, and as it is applied today by the most experienced programmers. Eric Raymond offers the next generation of hackers the unique opportunity to learn the connection between UNIX philosophy and practice through careful case studies of the very best UNIX/Linux programs.

    Before we delve into the intricacies of JavaScript, we need to know why it is used. While HTML tells your browser how your webpage will look, JavaScript is used for dynamic content and to add functionality. Using this book, you will understand the concept of JavaScript and its use in web designing. You will also have a look at jQuery in general. You will learn about Functions, Operators, the concept of Variables, Conditions and Loops, Arrays, and the basics of jQuery in this book. Instead of wandering through loads of theory, we have used practical examples in this book. The examples in this book are compatible with almost every browser. Instead of using the verbatim code, you can modify the code and see the change in the output thereby understanding the subtle nuances of JavaScript. By the end of the book, with practice, you can achieve better things and get more acquainted with JavaScript.