Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) by Eibe Frank
Introduction to Physical Science, Revised Edition, 12th Edition, James T. Shipman, Jerry D. Wilson, Aaron W. Todd, CENGAGE, IRM(IM)+LAB MANUAL
ICSE Board Computer Science Text Books
DEPARTMENT OF COMPUTER SCIENCE AND INDUSTRIAL TECHNOLOGY
ICSE Computer Science books
Environmental Science, 13th Edition, G. Tyler Miller Jr., Scott Spoolman,Test Bank
USING AN INNOVATIVE PEDAGOGICAL APPROACH TO CREATE AND ENHANCE INTRINSIC MOTIVATION TO STIMULATE LEARNING
AN ADAPTIVE GMM APPROACH TO BACKGROUND SUBTRACTION FOR APPLICATION IN REAL TIME SURVEILLANCE
AN EXCESS SPREAD APPROACH TO NONPARTICIPATING INSURANCE PRODUCTS
An Examination of How Hospitals Use the Reporting Framework Prescribed in the Ontario Hospital Reporting System
Until recently, all of the interactions between objects in virtual 3D worlds have been based on calculations performed using linear algebra. Linear algebra relies heavily on coordinates, however, which can make many geometric programming tasks very specific and complex-often a lot of effort is required to bring about even modest performance enhancements. Although linear algebra is an efficient way to specify low-level computations, it is not a suitable high-level language for geometric programming. Geometric Algebra for Computer Science presents a compelling alternative to the limitations of linear algebra. Geometric algebra, or GA, is a compact, time-effective, and performance-enhancing way to represent the geometry of 3D objects in computer programs. In this book you will find an introduction to GA that will give you a strong grasp of its relationship to linear algebra and its significance for your work. You will learn how to use GA to represent objects and perform geometric operations on them. And you will begin mastering proven techniques for making GA an integral part of your applications in a way that simplifies your code without slowing it down.
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