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.

    It can also serve as a one-semester introductory course at the beginning graduate level, as a useful precursor to a more serious study of CFD in advanced books. It is presented in a very readable, informal, enjoyable style.

    Python, an easy-to-learn and increasingly popular object-oriented language, allows readers to become comfortable with the fundamentals of programming without the troublesome syntax that can be challenging for novices. With the knowledge acquired using Python, students gain confidence in their skills and learn to recognize the logic behind developing high-quality programs. Starting Out with Python discusses control structures, functions, arrays, and pointers before objects and classes. As with all Gaddis texts, clear and easy-to-read code listings, concise and practical real-world examples, detail-oriented explanations, and an abundance of exercises appear in every chapter. This text is intended for a one-semester introductory programming course for students with limited programming experience.

    Our inaugural effort is OpenIntro Statistics. Probability is optional, inference is key, and we feature real data whenever possible. Files for the entire book are freely available at openintro.org, and anybody can purchase a paperback copy from amazon.com for under $10.The future for OpenIntro depends on the involvement and enthusiasm of our community. Visit our website, openintro.org. We provide free course management tools, including an online question bank, utilities for creating course quizzes, and many other helpful resources.CERTAIN CONTENT THAT APPEARS ON THIS SITE COMES FROM AMAZON SERVICES LLC. THIS CONTENT IS PROVIDED ‘AS IS’ AND IS SUBJECT TO CHANGE OR REMOVAL AT ANY TIME.Can’t find it here? Search Amazon.com Search: All Products Apparel & AccessoriesBabyBeautyBooksCamera & PhotoCell Phones & ServiceClassical MusicComputersComputer & Video GamesDVDElectronicsGourmet FoodHome & GardenMiscellaneousHealth & Personal CareJewelry & WatchesKitchen & HousewaresMagazine SubscriptionsMusicMusical InstrumentsSoftwareSports & OutdoorsTools & HardwareToys & GamesVHS Keywords:

    The presentation stresses analytical methods, concrete examples, and geometric intuition. A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with mathematical theory.About the Author:Steven Strogatz is in the Center for Applied Mathematics and the Department of Theoretical and Applied Mathematics at Cornell University. Since receiving his Ph.D. from Harvard university in 1986, Professor Strogatz has been honored with several awards, including the E.M. Baker Award for Excellence, the highest teaching award given by MIT.

    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.

    KEY TOPICS: Written in a reader-friendly style, the book encourages broad problem-solving skills while thoroughly covering the material required for introductory algorithms. The author emphasizes conceptual understanding before the introduction of the formal treatment of each technique. Popular puzzles are used to motivate readers' interest and strengthen their skills in algorithmic problem solving. Other enhancement features include chapter summaries, hints to the exercises, and a solution manual. MARKET: For those interested in learning more about algorithms.

    Topics cover every aspect of radio communication, including basic system and procedural comprehension, etiquette and rules, visual flight rules, instrument flight rules, emergency procedures, ATC facilities and their functions, and a review of airspace definitions. This revised edition also discusses Global Positioning Systems (GPS) and Land and Hold Short Operations (LAHSO). Beginners and professionals alike will find this an invaluable resource for communicating by radio.

    Provides a review of introductory noncalculus-based physics for those who do not have a strong background in mathematics.

    0321513339 / 9780321513335 Physics for Scientists and Engineers: A Strategic Approach with Modern Physics and MasteringPhysicsâ�¢ Package consists of 0321513576 / 9780321513571 Student Workbook for Physics for Scientists and Engineers: A Strategic Approach with Modern Physics 0321516397 / 9780321516398 MasteringPhysicsâ�¢ with E-book Student Access Kit for Physics for Scientists and Engineers: A Strategic Approach 0805327363 / 9780805327366 Physics for Scientists and Engineers: A Strategic Approach with Modern Physics

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.

     At any given moment, somewhere in the world someone struggles with the same software design problems you have. You know you don't want to reinvent the wheel (or worse, a flat tire), so you look to Design Patterns--the lessons learned by those who've faced the same problems. With Design Patterns, you get to take advantage of the best practices and experience of others, so that you can spend your time on...something else. Something more challenging. Something more complex. Something more fun. You want to learn about the patterns that matter--why to use them, when to use them, how to use them (and when NOT to use them). But you don't just want to see how patterns look in a book, you want to know how they look "in the wild". In their native environment. In other words, in real world applications. You also want to learn how patterns are used in the Java API, and how to exploit Java's built-in pattern support in your own code. You want to learn the real OO design principles and why everything your boss told you about inheritance might be wrong (and what to do instead). You want to learn how those principles will help the next time you're up a creek without a design pattern. Most importantly, you want to learn the "secret language" of Design Patterns so that you can hold your own with your co-worker (and impress cocktail party guests) when he casually mentions his stunningly clever use of Command, Facade, Proxy, and Factory in between sips of a martini. You'll easily counter with your deep understanding of why Singleton isn't as simple as it sounds, how the Factory is so often misunderstood, or on the real relationship between Decorator, Facade and Adapter. With Head First Design Patterns, you'll avoid the embarrassment of thinking Decorator is something from the "Trading Spaces" show. Best of all, in a way that won't put you to sleep! We think your time is too important (and too short) to spend it struggling with academic texts. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. Using the latest research in neurobiology, cognitive science, and learning theory, Head First Design Patterns will load patterns into your brain in a way that sticks. In a way that lets you put them to work immediately. In a way that makes you better at solving software design problems, and better at speaking the language of patterns with others on your team.

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    The book teaches the basic tools for the design of digital circuits in a clear, easily accessible manner. New to This Edition: *Nine sections on Verilog Hardware Description Language (HDL) inserted in discrete sections, allowing the material to be covered or skipped as desired. The Verilog HDL presentation is at a suitable level for beginning students who are learning digital circuits for the first time. *Reorganized material on combinational circuits is now covered in a single chapter. *The emphasis in the sequential circuits chapters is now on design with D flip-flops instead of JK and SR flip-flops. *The material on memory and programmable logic is now consolidated in one chapter. *Chapter 8 consists mostly of new material and now covers digital design in the Register Transfer Level (P) FL), preparing the reader for more advanced design projects and further Verilog HDL studies. *A new section in Chapter 11 supplements the laboratory experiments with HDL experiments. These unable the reader to check the circuits designed in the laboratory by means of hardware components and/or by HDL simulation.* Text accompanied by Verilog simulator software-SynaptiCAD's VeriLogger Pro evaluation version, a Verilog simulation environment that combines all of the features of a traditional Verilog simulator with a powerful graphical test vector generator. Fast model testing in VeriLogger Pro allows the reader to perform bottom-up testing of every model in a design. All of the HDL examples in the book can be found on the CD-ROM. *A Companion Website includes resources for instructors and students such as transparency masters of all figures in the book, all HDL code examples from the book, a Verilog tutorial, tutorials on using the VeriLogger Pro software, and more. It can be found at http://www.prenhall.com/mano