Linear Algebra


Kenneth M. Hoffman - 1971
    Linear Equations; Vector Spaces; Linear Transformations; Polynomials; Determinants; Elementary canonical Forms; Rational and Jordan Forms; Inner Product Spaces; Operators on Inner Product Spaces; Bilinear Forms For all readers interested in linear algebra.

An Introduction to Statistical Learning: With Applications in R


Gareth James - 2013
    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering


Steven H. Strogatz - 1994
    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.

The Laws of Thermodynamics: A Very Short Introduction


Peter Atkins - 1990
    From the sudden expansion of a cloud of gas to the cooling of hot metal--everything is moved or restrained by four simple laws. Written by Peter Atkins, one of the world's leading authorities on thermodynamics, this powerful and compact introduction explains what these four laws are and how they work, using accessible language and virtually no mathematics. Guiding the reader a step at a time, Atkins begins with Zeroth (so named because the first two laws were well established before scientists realized that a third law, relating to temperature, should precede them--hence the jocular name zeroth), and proceeds through the First, Second, and Third Laws, offering a clear account of concepts such as the availability of work and the conservation of energy. Atkins ranges from the fascinating theory of entropy (revealing how its unstoppable rise constitutes the engine of the universe), through the concept of free energy, and to the brink, and then beyond the brink, of absolute zero. About the Series: Combining authority with wit, accessibility, and style, Very Short Introductions offer an introduction to some of life's most interesting topics. Written by experts for the newcomer, they demonstrate the finest contemporary thinking about the central problems and issues in hundreds of key topics, from philosophy to Freud, quantum theory to Islam.

The Good Listener


James E. Sullivan - 2000
    Readers learn the effects that their listening has on others and insight into the effects that the listening skills of others have upon them.

Case Files: Pediatrics


Eugene C. Toy - 2003
    Each case includes an extended discussion, definition of terms, clinical pearls, and USMLE format review questions. This interactive learning system helps you understand essential concepts instead of memorizing facts.

Engineering Mechanics: Dynamics (Volume 2)


J.L. Meriam - 1952
    It illustrates both the cohesiveness of the relatively few fundamental ideas in this area and the great variety of problems these ideas solve. All of the problems address principles and procedures inherent in the design and anlysis of engineering structures and mechanical systems, with many of the problems referring explicitly to design considerations.

Theory of machines


S.S. Rattan - 2009
    

Calculus [With CDROM]


James Stewart - 1986
    Stewart's Calculus is successful throughout the world because he explains the material in a way that makes sense to a wide variety of readers. His explanations make ideas come alive, and his problems challenge, to reveal the beauty of calculus. Stewart's examples stand out because they are not just models for problem solving or a means of demonstrating techniques--they also encourage readers to develp an analytic view of the subject. This edition includes new problems, examples, and projects.

Modern Control Engineering


Katsuhiko Ogata - 1970
    The layout of the book covers the following: Laplace transforms, mathematical model

Managerial Accounting: Tools for Business Decision Making


Jerry J. Weygandt - 1999
    Aimed at accountants or readers of other career paths, this book helps them build their decision making skills and understand how to use accounting information to make quality business decisions.

Practical Algebra: A Self-Teaching Guide


Peter H. Selby - 1974
    Practical Algebra is an easy andfun-to-use workout program that quickly puts you in command of allthe basic concepts and tools of algebra. With the aid of practical, real-life examples and applications, you'll learn: * The basic approach and application of algebra to problemsolving * The number system (in a much broader way than you have known itfrom arithmetic) * Monomials and polynomials; factoring algebraic expressions; howto handle algebraic fractions; exponents, roots, and radicals;linear and fractional equations * Functions and graphs; quadratic equations; inequalities; ratio, proportion, and variation; how to solve word problems, andmore Authors Peter Selby and Steve Slavin emphasize practical algebrathroughout by providing you with techniques for solving problems ina wide range of disciplines--from engineering, biology, chemistry, and the physical sciences, to psychology and even sociology andbusiness administration. Step by step, Practical Algebra shows youhow to solve algebraic problems in each of these areas, then allowsyou to tackle similar problems on your own, at your own pace.Self-tests are provided at the end of each chapter so you canmeasure your mastery.

Tesla Motors: How Elon Musk and Company Made Electric Cars Cool, and Sparked the Next Tech Revolution


Charles Morris - 2014
    The most trusted sources in the auto industry have called its Model S the most advanced, safest and best-performing car ever built - and it doesn’t use a drop of gasoline. Tesla has changed the way the public perceives electric vehicles, and inspired the major automakers to revive their own dormant efforts to sell EVs. However, even amidst the avalanche of media coverage that followed the triumph of the Model S, few have grasped the true significance of what is happening. Tesla has redefined the automobile, sparked a new wave of innovation comparable to the internet and mobile computing revolutions, and unleashed forces that will transform not just the auto industry, but every aspect of society. The Tesla story is one part of an ongoing tide of change driven by the use of information technology to eliminate “friction” such as geographic distance, middlemen and outdated regulations. Tesla is simply applying the new order to the auto industry, but the automobile is such a pervasive influence in our lives that redefining how it is designed, built, driven and sold will have sweeping effects in unexpected areas. Just as Tesla built the Model S as an electric vehicle “from the ground up,” it has taken an outsider’s approach to the way it markets its cars. Its direct sales model has drawn legal challenges from entrenched auto dealers, who fear that their outdated business model will be destroyed. Its systems approach to the software and electronics in its cars has highlighted how far behind the technological times the major automakers are. It’s easy to see why readers find Tesla irresistible. CEO Elon Musk is a superstar entrepreneur, a “nauseatingly pro-US” immigrant and the leader of two other cutting-edge companies. Tesla dares to challenge the establishment behemoths and, so far at least, has handily beaten them at their own game. In this history of the 21st century’s most exciting startup, Charles Morris begins with a brief history of EVs and a biography of Tesla’s driving force, Elon Musk. He then details the history of the company, told in the words of the Silicon Valley entrepreneurs who made it happen. There are many fascinating stories here: Martin Eberhard’s realization that there were many like himself, who loved fast cars but wanted to help the environment and bring about the post-oil age; the freewheeling first days, reminiscent of the early internet era; the incredible ingenuity of the team who built the Roadster; Tesla’s near-death experience and miraculous resurrection; the spiteful split between the company’s larger-than-life leaders; the gloves-off battles with hostile media such as Top Gear and the New York Times; and the media’s ironic about-face when the magnificent Model S won the industry’s highest honors, and naysayers became cheerleaders overnight. And the story is just beginning: Tesla has breathtakingly ambitious plans for the future.This book was updated May 1, 2015 to include the latest on the Gigafactory and the D package.

Thomas' Calculus, Early Transcendentals, Media Upgrade


George B. Thomas Jr. - 2002
    This book offers a full range of exercises, a precise and conceptual presentation, and a new media package designed specifically to meet the needs of today's readers. The exercises gradually increase in difficulty, helping readers learn to generalize and apply the concepts. The refined table of contents introduces the exponential, logarithmic, and trigonometric functions in Chapter 7 of the text.KEY TOPICS Functions, Limits and Continuity, Differentiation, Applications of Derivatives, Integration, Applications of Definite Integrals, Integrals and Transcendental Functions, Techniques of Integration, Further Applications of Integration, Conic Sections and Polar Coordinates, Infinite Sequences and Series, Vectors and the Geometry of Space, Vector-Valued Functions and Motion in Space, Partial Derivatives, Multiple Integrals, Integration in Vector Fields.MARKET For all readers interested in Calculus.

Pattern Recognition and Machine Learning


Christopher M. Bishop - 2006
    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.