While equipping you with the minimum of theory, GUI expert Jeff Johnson presents the reality of interface design in an entertaining, anecdotal, and instructive way. * Updated to reflect the bloopers that are common today, incorporating many comments and suggestions from first edition readers. * Takes a learn-by-example approach that teaches how to avoid common errors. * Covers bloopers in a wide range of categories: GUI controls, graphic design and layout, text messages, interaction strategies, Web site design -- including search, link, and navigation, responsiveness issues, and management decision-making. * Organized and formatted so information needed is quickly found, the new edition features call-outs for the examples and informative captions to enhance quick knowledge building. * Hundreds of illustrations: both the DOs and the DON'Ts for each topic covered, with checklists and additional bloopers on www.gui-bloopers.com.

    The first edition of this book, Programming Perl, hit the shelves in 1990, and was quickly adopted as the undisputed bible of the language. Since then, Perl has grown with the times, and so has this book.Programming Perl is not just a book about Perl. It is also a unique introduction to the language and its culture, as one might expect only from its authors. Larry Wall is the inventor of Perl, and provides a unique perspective on the evolution of Perl and its future direction. Tom Christiansen was one of the first champions of the language, and lives and breathes the complexities of Perl internals as few other mortals do. Jon Orwant is the editor of The Perl Journal, which has brought together the Perl community as a common forum for new developments in Perl.Any Perl book can show the syntax of Perl's functions, but only this one is a comprehensive guide to all the nooks and crannies of the language. Any Perl book can explain typeglobs, pseudohashes, and closures, but only this one shows how they really work. Any Perl book can say that my is faster than local, but only this one explains why. Any Perl book can have a title, but only this book is affectionately known by all Perl programmers as "The Camel."This third edition of Programming Perl has been expanded to cover version 5.6 of this maturing language. New topics include threading, the compiler, Unicode, and other new features that have been added since the previous edition.

    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 practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

    Collected from the series of blog posts starting at: https://bartoszmilewski.com/2014/10/2...Hardcover available at: http://www.blurb.com/b/9008339-catego...

    Where did I go wrong?" Most instructors hear this complaint every year. In many cases, it is true that the student invested countless hours, only to produce abysmal results. Often, inefficient study habits are to blame. The important question is: why do so many students have difficulty preparing themselves for organic chemistry exams? There are certainly several factors at play here, but perhaps the most dominant factor is a fundamental disconnect between what students learn and the tasks expected of them. To address the disconnect in organic chemistry instruction, David Klein has developed a textbook that utilizes a skills-based approach to instruction. The textbook includes all of the concepts typically covered in an organic chemistry textbook, but special emphasis is placed on skills development to support these concepts. This emphasis upon skills development will provide students with a greater opportunity to develop proficiency in the key skills necessary to succeed in organic chemistry.As an example, resonance structures are used repeatedly throughout the course, and students must become masters of resonance structures early in the course. Therefore, a significant portion of chapter 1 is devoted to drawing resonance structures.Two chapters (6 and 12) are devoted almost entirely to skill development. Chapter 6 emphasizes skills that are necessary for drawing mechanisms, while chapter 12 prepares the student for proposing syntheses.In addition, each chapter contains numerous Skillbuilders, each of which is designed to foster a specific skill. Each skillbuildercontains three parts:1. Learn the Skill: a solved problem that demonstrates a particular skill;2. Practice the Skill: numerous problems (similar to the solved problem) that give the students an opportunity to practice and master the skill;3. Apply the Skill: one or two more-challenging problems in which the student must apply the skill in a slightly different environment. These problems include conceptual, cumulative, and applied problems that encourage students to think out of the box. Sometimes problems that foreshadow concepts introduced in later chapters are also included.All SkillBuilders are visually summarized at the end of each chapter (Skillbuilder review), followed by a list of suggested in-chapter and end-of-chapter practice problems.

    The main objective of this book is to present circuit analysis in a clear, easy-to-understand manner, with many practical applications to interest the student. Each chapter opens with either historical sketches or career information on a subdiscipline of electrical engineering. This is followed by an introduction that includes chapter objectives. Each chapter closes with a summary of the key points and formulas. The authors present principles in an appealing and lucid step-by-step manner, carefully explaining each step. Important formulas are highlighted to help students sort out what is essential and what is not. Many pedagogical aids reinforce the concepts learned in the text so that students get comfortable with the various methods of analysis presented in the text.

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

    'Systems Analysis and Design' is a human-centred book that concisely presents the latest systems development methods, tools and techniques to students in an engaging and easy-to-understand manner.

    Admittedly, computers now play chess at the grandmaster level, but do they understand the game as we do? Can a computer eventually do everything a human mind can do? In this absorbing and frequently contentious book, Roger Penrose--eminent physicist and winner, with Stephen Hawking, of the prestigious Wolf prize--puts forward his view that there are some facets of human thinking that can never be emulated by a machine. Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness. He is among a growing number of physicists who think Einstein wasn't being stubborn when he said his little finger told him that quantum mechanics is incomplete, and he concludes that laws even deeper than quantum mechanics are essential for the operation of a mind. To support this contention, Penrose takes the reader on a dazzling tour that covers such topics as complex numbers, Turing machines, complexity theory, quantum mechanics, formal systems, Godel undecidability, phase spaces, Hilbert spaces, black holes, white holes, Hawking radiation, entropy, quasicrystals, the structure of the brain, and scores of other subjects. The Emperor's New Mind will appeal to anyone with a serious interest in modern physics and its relation to philosophical issues, as well as to physicists, mathematicians, philosophers and those on either side of the AI debate.

    The layout of the book covers the following: Laplace transforms, mathematical model

    In the second edition of Network Security, this most distinguished of author teams draws on hard-won experience to explain every facet of information security, from the basics to advanced cryptography and authentication; secure Web and email services; and emerging security standards. Highlights of the book's extensive new coverage include Advanced Encryption Standard (AES), IPsec, SSL, PKI Standards, and Web security.