Included are discussions on: cinematic time and space; compositional rules; and types of editing.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    But do you know how to use them to their greatest possible advantage? Only now, with the publication of Linkers & Loaders, is there an authoritative book devoted entirely to these deep-seated compile-time and run-time processes. The book begins with a detailed and comparative account of linking and loading that illustrates the differences among various compilers and operating systems. On top of this foundation, the author presents clear practical advice to help you create faster, cleaner code. You'll learn to avoid the pitfalls associated with Windows DLLs, take advantage of the space-saving, performance-improving techniques supported by many modern linkers, make the best use of the UNIX ELF library scheme, and much more. If you're serious about programming, you'll devour this unique guide to one of the field's least understood topics. Linkers & Loaders is also an ideal supplementary text for compiler and operating systems courses.

    The new edition includes the most up-to-date research developments and many more examples and problems.

    This second edition brings you up to date on recent changes in search engine behavior—such as new ranking methods involving user engagement and social media—with an array of effective tactics, from basic to advanced.Comprehend SEO’s many intricacies and complexitiesExplore the underlying theory and inner workings of search enginesUnderstand the role of social media, user data, and linksDiscover tools to track results and measure successRecognize how changes to your site can confuse search enginesLearn to build a competent SEO team with defined rolesGlimpse the future of search and the SEO industry

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    This is a hands-on guide to mastering Objective C - the language every MAC OS X and iPhone/iPod Touch developer needs to know.

    Those principles included modern theories of atomic and molecular structure, quantum mechanics, statistical mechanics and thermodynamics. In addition, Dr. Pauling attempted to correlate the theories with descriptive chemistry, the observed properties of substances, to introduce the student to the multitude of chemical substances and their properties.In this extensively revised and updated third edition, the Nobel prizewinning author maintains an excellent balance between theoretical and descriptive material, although the amount of descriptive chemistry has been decreased somewhat, and the presentation of the subject, especially in relation to the nonmetals, has been revised in such a way as to permit greater correlation with the electronic structure of atoms, especially electronegativity. The principles of quantum mechanics are discussed on the basis of the de Broglie wavelength of the electron. The quantized energy levels of a particle in a box are derived by means of a simple assumption about the relation of the de Broglie waves to the walls of the box. No attempt is made to solve the Schrödinger wave equation for other systems, but the wave functions of hydrogen-like electrons are presented and discussed in some detail, and the quantum states for other systems are also covered. Statistical mechanics is introduced before thermodynamics, and the discussion of thermodynamics is based on it. This arrangement reflects the author's belief that beginning students can understand statistical mechanics better than chemical thermodynamics. Aimed at first-year college students who plan to major in chemistry or closely related fields, the book is written in a logical, clear and understandable style. In addition, many excellent figures are included, along with numerous problems and 75 pages of appendixes covering such topics as symmetry of molecules and crystals, hybrid bond orbitals, and magnetic properties of substances.

    The Authors Discuss The Mathematical Theory In Detail And Then Provide The Geometric Interpretation Necessary To Make 3D Math Intuitive. Working C++ Classes Illustrate How To Put The Techniques Into Practice, And Exercises At The End Of Each Chapter Help Reinforce The Concepts. This Book Explains Basic Concepts Such As Vectors, Coordinate Spaces, Matrices, Transformations, Euler Angles, Homogenous Coordinates, Geometric Primitives, Intersection Tests, And Triangle Meshes. It Discusses Orientation In 3D, Including Thorough Coverage Of Quaternions And A Comparison Of The Advantages And Disadvantages Of Different Representation Techniques. The Text Describes Working C++ Classes For Mathematical And Geometric Entities And Several Different Matrix Classes, Each Tailored To Specific Geometric Tasks. Also Included Are Complete Derivations For All The Primitive Transformation Matrices.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Stressing the relationship between system software and the architecture of the machine it is designed to support, Beck first presents the fundamental concepts and basic design of each type of software in a machine-independent way. He then discusses both machine-dependent and independent extensions to the basic concepts, and gives examples of the actual system software. New FeaturesProvides updated architecture and software examples, including the Intel x86 family (Pentium, P6, etc.), IBM PowerPC, Sun SPARC, and Cray T3E. Includes an introduction to object-oriented programming and design, and illustrates these concepts of object-oriented languages, compilers, and operating systems. Brings the book up-to-speed with industry by including current operating systems topics, such as multiprocessor, distributed, and client/server systems. Contains a wide selection of examples and exercises, providing teaching support as well as flexibility, allowing you to concentrate on the software and architectures that you want to cover.

    

    With its unique combination of Japanese-style comics called manga and serious educational content, the EduManga format is already a hit in Japan.In The Manga Guide to Statistics, our heroine Rui is determined to learn about statistics to impress the dreamy Mr. Igarashi and begs her father for a tutor. Soon she's spending her Saturdays with geeky, bespectacled Mr. Yamamoto, who patiently teaches her all about the fundamentals of statistics: topics like data categorization, averages, graphing, and standard deviation.After all her studying, Rui is confident in her knowledge of statistics, including complex concepts like probability, coefficients of correlation, hypothesis tests, and tests of independence. But is it enough to impress her dream guy? Or maybe there's someone better, right in front of her?Reluctant statistics students of all ages will enjoy learning along with Rui in this charming, easy-to-read guide, which uses real-world examples like teen magazine quizzes, bowling games, test scores, and ramen noodle prices. Examples, exercises, and answer keys help you follow along and check your work. An appendix showing how to perform statistics calculations in Microsoft Excel makes it easy to put Rui's lessons into practice.This EduManga book is a translation from a bestselling series in Japan, co-published with Ohmsha, Ltd. of Tokyo, Japan.

    From your first steps of learning about WordPress all the way through maintaining a site throughout the years, this book is packed with truly practical information.

    Twenty-five years later, the book still stands as the reference for mental health professionals who incorporate art into their practice. Now, with the publication of this fully updated and revised Twenty-Fifth Anniversary Edition, which includes a DVD that illustrates art therapy techniques in actual therapy settings, this pioneering guide is available to train, inform, and inspire a new generation of art therapists and those seeking to introduce art therapy into their clinical practice.The text illustrates how to: Set the conditions for creative growth, assess progress, and set goals for therapy Use art in individual, group, and family situations, including parent-child pairings, mothers' groups, and adolescent groups Work with healthy children and those with disabilities Guide parents through art and play Talk about art work and encourage art production Decode nonverbal messages contained in art and the art-making process Use scribbles, drawings, stories, poems, masks, and other methods to facilitate expression Understand why and how art therapy works Along with the useful techniques and activities described, numerous case studies taken from Rubin's years of practice add a vital dimension to the text, exploring how art therapy works in the real world of children's experience. Original artwork from clients and the author illuminate the material throughout. Written by an internationally recognized art therapist, Child Art Therapy, Twenty-Fifth Anniversary Edition is a comprehensive guide for learning about, practicing, and refining child art therapy.