"More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    Divided into five parts computer and data, computer hardware, computer software, data organization and with an introduction to some of the more advanced topics Foundations of Computer Science gives students a bird's eye view of the subject. Each chapter includes key terms, summaries, review questions, multiple-choice questions, and exercises to enhance learning, while introducing tools such as UML, structure chart and pseudocode, which students will need in order to succeed in later courses. The text is also supported by numerous figures, examples, exercises, selected solutions and a test bank, all designed to ease and aid the learning process. Updated to cover the latest technologies and changes to course requirements, this second edition features new and updated coverage of: Artificial Intelligence, Computer Ethics and Crimes, Networking, LINUX, and Security.

    It includes even more new monographs and the latest FDA approvals. This updated edition is a book that students can count on with vital information for Peds, as well as precautions for all vulnerable populations. From pediatrics to geriatrics and from pregnancy to breast feeding considerations, "Davis's Drug Guide for Nurses" addresses the entire lifespan.

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently. Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.

    Verification that algorithms work is emphasized more than their complexity. An effective use of examples, and huge number of interesting exercises, demonstrate the topics of trees and distance, matchings and factors, connectivity and paths, graph coloring, edges and cycles, and planar graphs. For those who need to learn to make coherent arguments in the fields of mathematics and computer science.

    With a new introduction, three new chapters, modernized language and methods throughout, and an appendix of challenging and enjoyable practice problems, Calculus Made Easy has been thoroughly updated for the modern reader.

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    Hundreds of thousands of Python developers around the world rely on Python for general-purpose tasks, Internet scripting, systems programming, user interfaces, and product customization. Available on all major computing platforms, including commercial versions of Unix, Linux, Windows, and Mac OS X, Python is portable, powerful and remarkable easy to use.With its convenient, quick-reference format, "Python Pocket Reference," 3rd Edition is the perfect on-the-job reference. More importantly, it's now been refreshed to cover the language's latest release, Python 2.4. For experienced Python developers, this book is a compact toolbox that delivers need-to-know information at the flip of a page. This third edition also includes an easy-lookup index to help developers find answers fast!Python 2.4 is more than just optimization and library enhancements; it's also chock full of bug fixes and upgrades. And these changes are addressed in the "Python Pocket Reference," 3rd Edition. New language features, new and upgraded built-ins, and new and upgraded modules and packages--they're all clarified in detail.The "Python Pocket Reference," 3rd Edition serves as the perfect companion to "Learning Python" and "Programming Python."

    It strikes a balance between theory and application by incorporating real examples, and helping students visualize the three-dimensional atomic and molecular structures that are the basis of chemical activity.

    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.

    A new foreword by Kip Thorne, the current Richard Feynman Professor of Theoretical Physics at Caltech, discusses the relevance of the new edition to today's readers. This boxed set also includes Feynman's new Tips on Physics—the four previously unpublished lectures that Feynman gave to students preparing for exams at the end of his course. Thus, this 4-volume set is the complete and definitive edition of The Feynman Lectures on Physics. Packaged in a specially designed slipcase, this 4-volume set provides the ultimate legacy of Feynman's extraordinary contribution to students, teachers, researches, and lay readers around the world.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    The new edition is thoroughly updated, including most notably a new chapter on innate immunity, a capstone chapter on immune responses in time and space, and many new focus boxes drawing attention to exciting clinical, evolutionary, or experimental connections that help bring the material to life.See what's in the LaunchPad

    This Eighth Edition redefines the high standard set by previous editions. It offers the best balance of rigor and accessibility, the most current research, and the most thorough technology integration available for your course--all presented within a unique modular format that supports student mastery and provides instructors with maximum teaching flexibility. In every chapter, Kalat accurately portrays biopsychology as a dynamic and empirical field in which fascinating new discoveries are constantly being made. He captures readers' interest with the latest biological psychology findings, such as how gingko biloba claims to aid memory and coverage of the hypothesis that humans' mate choice patterns are influenced by natural selection. Throughout, the author's goal is not only to convey information, but also to convey his excitement about and dedication to the subject.