Its humorous title begins with the punch line of a classic joke about someone who is baffled by technology. It was written by a 40-year computer veteran who wants to take the mystery out of computers and allow everyone to gain a true understanding of exactly what computers are, and also what they are not. Years of writing, diagramming, piloting and editing have culminated in one easy to read volume that contains all of the basic principles of computers written so that everyone can understand them. There used to be only two types of book that delved into the insides of computers. The simple ones point out the major parts and describe their functions in broad general terms. Computer Science textbooks eventually tell the whole story, but along the way, they include every detail that an engineer could conceivably ever need to know. Like Momma Bear's porridge, But How Do It Know? is just right, but it is much more than just a happy medium. For the first time, this book thoroughly demonstrates each of the basic principles that have been used in every computer ever built, while at the same time showing the integral role that codes play in everything that computers are able to do. It cuts through all of the electronics and mathematics, and gets right to practical matters. Here is a simple part, see what it does. Connect a few of these together and you get a new part that does another simple thing. After just a few iterations of connecting up simple parts - voilà! - it's a computer. And it is much simpler than anyone ever imagined. But How Do It Know? really explains how computers work. They are far simpler than anyone has ever permitted you to believe. It contains everything you need to know, and nothing you don't need to know. No technical background of any kind is required. The basic principles of computers have not changed one iota since they were invented in the mid 20th century. "Since the day I learned how computers work, it always felt like I knew a giant secret, but couldn't tell anyone," says the author. Now he's taken the time to explain it in such a manner that anyone can have that same moment of enlightenment and thereafter see computers in an entirely new light.

    The text shows you how to use statistical methods to design and develop new products, and new manufacturing systems and processes. You'll gain a better understanding of how these methods are used in everyday work, and get a taste of practical engineering experience through real-world, engineering-based examples and exercises. Now revised, this Fourth Edition of "Applied Statistics and Probability for Engineers" features many new homework exercises, including a greater variation of problems and more computer problems.

    Shows how any proof can be understood as a sequence of techniques. Covers the full range of techniques used in proofs, such as the contrapositive, induction, and proof by contradiction. Explains how to identify which techniques are used and how they are applied in the specific problem. Illustrates how to read written proofs with many step-by-step examples. Includes new, expanded appendices related to discrete mathematics, linear algebra, modern algebra and real analysis.

    This is type of problems asked at the JEE (IIT). The purpose of this book is to show students how to handle such problems and give them sufficient practice in solving problems of this type, thus building their confidence. The main features of this book are:Each chapter begins with a summary of facts, formulate and working techniques. Trick, tips and techniques have been clearly marked with the icon.A large number of problems have been solved and explained in each chapter.The exercises contain short-answer, long-answer and objective type questions.Multiple-choice questions in which more than one option may be correct have also been given.Time-bound tests at the end of each chapter will help students practise answering questions in a given time.The book also includes integrated tests, bases on all the chapters.A chapter containing miscellaneous problems has been given at the end of the book. This will help students gain confidence in solving problems without prior knowledge of the chapter(s) to which the problems belong.Table of ContentsAlgebraProgressions, Related Inequalities and SeriesDeterminants and Cramer's RuleEquations, Inequations and ExpressionsComplex NumbersPermutation and CombinationBinomial Theorem for Positive Integral IndexPrinciple of Mathematical Induction (PMI)Infinite SeriesMatricesTrigonometryCircular Functions, IdentitiesSolution of EquationsInverse Circular FunctionsTrigonometrical Inequalities and InequationsLogarithmProperties of TriangleHeights and DistancesCoordinate GeometryCoordinates and Straight LinesPairs of Straight Lines and Transformation of AxesCirclesParabolaEllipse and HyperbolaCalculusFunctionDifferentiationLimit, Indeterminate FormContinuity, Differentiability and Graph of FunctionApplication of dy/dxMaxima and MinimaMonotonic Function and Lagrange's TheoremIndefinite In

    Here are 25 stories of science fiction that push the boundaries, by the biggest names in an emerging crop of high-tech futuristic writers including Charles Stross, Robert Reed, Alastair Reynolds, Peter Hamilton and Neal Asher.

    

    

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    It reveals the attraction that has drawn leading mathematicians and amateurs alike to number theory over the course of history.

    Viraf J. Dalal is the most popular Chemistry textbook prescribed by over 1600 ICSE Schools in India. It is 100% as per the latest ICSE Syllabus.

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

    It is highly recommended for anyone planning to study advanced analysis, e.g., complex variables, differential equations, Fourier analysis, numerical analysis, several variable calculus, and statistics. It is also recommended for future secondary school teachers. A limited number of concepts involving the real line and functions on the real line are studied. Many abstract ideas, such as metric spaces and ordered systems, are avoided. The least upper bound property is taken as an axiom and the order properties of the real line are exploited throughout. A thorough treatment of sequences of numbers is used as a basis for studying standard calculus topics. Optional sections invite students to study such topics as metric spaces and Riemann-Stieltjes integrals.

    1: Elementary Theory and Problems contains the essential material that is usually covered in required courses of strength of materials in our engineering schools. Strength of Materials - Part. 2: Advanced Theory and Problems contains the later developments that are of practical importance in the fields of strength of materials, and theory of elasticity. Complete derivations of problems of practical interest are given in most cases. The books are illustrated with a number of problems to which solutions are presented. In many cases, the problems are chosen so as to widen the field covered by the text and to illustrate the application of the theory in the solution of design problems.

    Its easy-to-read treatment offers an intuitive approach, featuring informal discussions followed by thematically arranged exercises. Intended for undergraduate courses in abstract algebra, it is suitable for junior- and senior-level math majors and future math teachers. This second edition features additional exercises to improve student familiarity with applications. An introductory chapter traces concepts of abstract algebra from their historical roots. Succeeding chapters avoid the conventional format of definition-theorem-proof-corollary-example; instead, they take the form of a discussion with students, focusing on explanations and offering motivation. Each chapter rests upon a central theme, usually a specific application or use. The author provides elementary background as needed and discusses standard topics in their usual order. He introduces many advanced and peripheral subjects in the plentiful exercises, which are accompanied by ample instruction and commentary and offer a wide range of experiences to students at different levels of ability.

    In this lively book of essays, Stephen Wolfram takes the reader along on some of his most surprising and engaging intellectual adventures in science, technology, artificial intelligence and language design.