It has become known for its engaging writing style, instructional art program and focus on active learning. We are so excited to offer a robust learning program with student-focused learning activities, allowing the student to manage their learning while you easily manage their assessment. Detailed reports show how your assignments measure various learning objectives from the book (or input your own!), levels of Bloom's Taxonomy or other categories, and how your students are doing. The Cowan Learning program will save you time and improve your student's success in this course.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    For courses in computer organization and architecture, this text provides a clear, comprehensive presentation of the organization and architecture of contemporary computers.

    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.

    This insightful overview provides striking examples of how these technologies have teamed up to give the Web a truly open platform.Author Kyle Simpson (HTML5 Cookbook) shows you how JavaScript unlocks the power of all of the new functionality in HTML5, giving web applications the capabilities developers have wanted for years. These technologies now provide the raw tools you need in the presentation layer to replace everything you used to do with Flash.You’ll discover how:> HTML5 builds natively into the web platform things we find most commonly useful, such as audio, video, and drawing> The Canvas element is changing graphic animations, games, audio visualization, charting, and video effects> Geolocation has spawned “geofencing” and augmented reality> Web Workers allows calculations to be performed in the background, rather than compete with the UI> Web Sockets is enabling realtime communication for chat, live tech support, multi-user collaboration, and gaming> Mobile device APIs will give web apps direct access the phone’s camera, vibration, and other capabilities

    Philosophy for Everyone begins by explaining what philosophy is before exploring the questions and issues at the foundation of this important subject.Key topics and their areas of focus include:Epistemology - what our knowledge of the world and ourselves consists in, and how we come to have it; Philosophy of Science - foundational conceptual issues in scientific research and practice; Philosophy of Mind - what it means for something to have a mind, and how minds should be understood and explained; Moral Philosophy - the nature of our moral judgements and reactions, whether they aim at some objective moral truth, or are mere personal or cultural preferences, and; Metaphysics - fundamental conceptual questions about the nature of reality.Designed to be used on the corresponding Introduction to Philosophy online course offered by The University of Edinburgh, this book is also highly recommended to anyone looking for a short overview of this fascinating discipline.

    Restructured into six parts, this new edition covers a wide spectrum of software processes from initial requirements solicitation through design and development.

    The bestselling textbook inorganic chemistry text on the market covers both theoretical and descriptive aspects of the subject, and emphasizes experimental methods, industrial applications, and modern topics.

    Problems are designed to progressively enhance MATLAB-use proficiency, so students need not be familiar with MATLAB at the start of your course. Program scripts that are answers to exercises in the text are available at no charge in electronic form (see Teaching Resources below). *Supplement and Review Mini-Chapters after each of the text's three parts contain an extensive review list of terms, test-like problem sets with answers, and detailed suggestions on supplemental reading to reinforce students' learning and help them prepare for exams. *Read-Only Chapters, strategically placed to provide a change of pace during the course, provide informative, yet enjoyable reading for students. *Measurement Details and Results samples offer students a realistic perspective on the seldom-perfect nature of device characteristics, contrary to the way they are often represented in introductory texts. Content Highlig

    By staying current, remaining relevant, and adapting to emerging course needs, this market-leading text has continued to define the operating systems course. This Seventh Edition not only presents the latest and most relevant systems, it also digs deeper to uncover those fundamental concepts that have remained constant throughout the evolution of today's operation systems. With this strong conceptual foundation in place, students can more easily understand the details related to specific systems. New Adaptations * Increased coverage of user perspective in Chapter 1. * Increased coverage of OS design throughout. * A new chapter on real-time and embedded systems (Chapter 19). * A new chapter on multimedia (Chapter 20). * Additional coverage of security and protection. * Additional coverage of distributed programming. * New exercises at the end of each chapter. * New programming exercises and projects at the end of each chapter. * New student-focused pedagogy and a new two-color design to enhance the learning process.

    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

    The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject.

    This new edition retains its basic organization. The three approaches - integral, differential, and dimensional analysis - are treated separately, providing the conceptual foundation of fluid mechanics. Chapters on ducts, immersed bodies, potential flow, compressible flow, open channels, and turbomachinery show the major applications of the field. The new edition includes a systematic problem solving methodology for readers to follow. New chapter examples and approximately 250 new chapter problems have been added. The EES (Engineering Equation Solver) software is included, free to users, as a means to model and solve problems on the computer. A new appendix offers a brief review of mathematical tools.

    Far from a dry, nuts-and-bolts exposition, however, 101 THINGS I LEARNED® IN ENGINEERING SCHOOL probes real-world examples to show how the engineer's way of thinking can-and sometimes cannot-inform our understanding of how things work. Questions from the simple to the profound are illuminated throughout: Why shouldn't soldiers march across a bridge? Why do buildings want to float and cars want to fly? What is the difference between thinking systemically and thinking systematically? How can engineering solutions sympathize with the natural environment? Presented in the familiar, illustrated format of the popular 101 THINGS I LEARNED® series, 101 THINGS I LEARNED® IN ENGINEERING SCHOOL offers an informative resource for students, general readers, and even experienced engineers, who will discover within many provocative new insights into familiar principles.

    An exceptional book written by a true professional.