'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

    This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics--particularly in machine learning, scientific modeling, and artificial life--and reviews a broad span of research, including the work of Mitchell and her colleagues.The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting general purpose nature of genetic algorithms as search methods that can be employed across disciplines.An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

    The salient features of the book are as follows: It exactly covers the prescribed syllabus. Nothing undesirable has been included and nothing essential has been left. Its approach is explanatory and language is lucid and communicable. The exposition of the subject matter is systematic and the students are better prepared to solve the problems. All fundamentals of the included topics are explained with a micro-analysis. Sufficient number of solved examples have been given to let the students understand the various skills necessary to solve the problems. These examples are well-graded. Unsolved exercises of multi-varieties have been given in a well-graded style. Attempting those on his own, will enable a student to create confidence and independence in him/her regarding the understanding of the subject. Daily life problems and practical applications have been incorporated in the body of the text. A large number of attractive and accurate figures have been drawn which enable a student to grasp the subject in an easier way. All the answers have been checked and verified. About The Author: N.P. Bali is a prolific author of over 100 books for degree and engineering students. He has been writing books for more than forty years. His books on the following topics are well known for their easy comprehension and lucid presentation: Algebra, Trigonometry, Differential Calculus, Integral Calculus, Real Analysis, Co-ordinate Geometry, Statics, Dynamics etc. Dr. Manish Goyal has been associated with

    All chapters are supplemented by thought-provoking problems. A useful work for graduate-level students with backgrounds in computer science, operations research, and electrical engineering. "Mathematicians wishing a self-contained introduction need look no further." — American Mathematical Monthly.

    Focused on helping students understand and construct proofs and expanding their mathematical maturity, this best-selling text is an accessible introduction to discrete mathematics. Johnsonbaugh's algorithmic approach emphasizes problem-solving techniques. The Seventh Edition reflects user and reviewer feedback on both content and organization.

    

    It moves beyond a mere study of algorithms without sacrificing the rigor that faculty desire. As in every edition, Winston reinforces the book's successful features and coverage with the most recent developments in the field. The Student Suite CD-ROM, which now accompanies every new copy of the text, contains the latest versions of commercial software for optimization, simulation, and decision analysis.

    Kurt Giidel maintained, and offered detailed proof, that in any arithmetic system, even in elementary parts of arithmetic, there are propositions which cannot be proved or disproved within the system. It is thus uncertain that the basic axioms of arithmetic will not give rise to contradictions. The repercussions of this discovery are still being felt and debated in 20th-century mathematics.The present volume reprints the first English translation of Giidel's far-reaching work. Not only does it make the argument more intelligible, but the introduction contributed by Professor R. B. Braithwaite (Cambridge University}, an excellent work of scholarship in its own right, illuminates it by paraphrasing the major part of the argument.This Dover edition thus makes widely available a superb edition of a classic work of original thought, one that will be of profound interest to mathematicians, logicians and anyone interested in the history of attempts to establish axioms that would provide a rigorous basis for all mathematics. Translated by B. Meltzer, University of Edinburgh. Preface. Introduction by R. B. Braithwaite.

    The Computer Revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before.But our love of computers should not cloud our thinking about their limitations.We are told that computers are smarter than humans and that data mining can identify previously unknown truths, or make discoveries that will revolutionize our lives. Our lives may well be changed, but not necessarily for the better. Computers are very good at discovering patterns, but are uselessin judging whether the unearthed patterns are sensible because computers do not think the way humans think.We fear that super-intelligent machines will decide to protect themselves by enslaving or eliminating humans. But the real danger is not that computers are smarter than us, but that we think computers are smarter than us and, so, trust computers to make important decisions for us.The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted.

    In the same period, the cross-fertilization of mathematics and philosophy resulted in a new sort of 'mathematical philosophy', associated most notably (but in different ways) with Bertrand Russell, W. V. Quine, and Godel himself, and which remains at the focus of Anglo-Saxon philosophical discussion. The present collection brings together in a convenient form the seminal articles in the philosophy of mathematics by these and other major thinkers. It is a substantially revised version of the edition first published in 1964 and includes a revised bibliography. The volume will be welcomed as a major work of reference at this level in the field.

    Including a selection of exercises, adjusted for this edition, at the end of each chapter, it offers a new and simpler treatment of the representability of recursive functions, a traditional stumbling block for students on the way to the Godel incompleteness theorems.

    In fact, AI will dramatically change our entire society.You might have heard that many jobs will be replaced by automation and robots, but did you also know that at the same time a huge number of new jobs will be created by AI?This book covers many fascinating and timely topics related to artificial intelligence, including: self-driving cars, robots, chatbots, and how AI will impact the job market, business processes, and entire industries, just to name a few.This book is divided into ten chapters:Chapter I: Introduction to Artificial IntelligenceChapter II: How Artificial Intelligence Is Changing Many IndustriesChapter III: How Artificial Intelligence Is Changing Business ProcessesChapter IV: Chatbots and How They Will Change CommunicationChapter V: How Artificial Intelligence Is Changing the Job MarketChapter VI: Self-Driving Cars and How They Will Change Traffic as We Know ItChapter VII: Robots and How They Will Change Our LivesChapter VIII: Artificial Intelligence Activities of Big Technology CompaniesChapter IX: Frequently Asked Questions About Artificial Intelligence Part IChapter X: Frequently Asked Questions About Artificial Intelligence Part IITo enhance your learning experience and help make the concepts easier to understand, there are more than 85 visual presentations included throughout the book.You will learn the answers to 101 questions about artificial intelligence, and also have access to a large number of resources, ideas and tips that will help you to understand how artificial intelligence will change our lives.Who is this book for?Managers and business professionalsMarketers and influencersEntrepreneurs and startupsConsultants and coachesEducators and teachersStudents and life-long learnersAnd everyone else who is interested in our future.Are you ready to discover how artificial intelligence will impact your life This guidebook offers a multitude of tools, techniques and strategies that every business and individual can quickly apply and benefit from.

    Be prepared to question the world you live in and everything you thought you knew about the universe, human origins, and the lost civilizations of the past. Discover thought-bending evidence from some of the oldest text ever written and learn the reasons why their content eventually became suppressed and hidden from most of society. Conspiracy theories or conspiracy facts, you decide what's real based on the evidence. Once you read The Stage of Time, your perspective on reality may never be quite the same way again. This book includes: -Details about the ancient civilizations that once existed around the world and the events which led to their disappearance. -Translations from ancient texts that include: The Atrahasis, Enuma Elish, Sumerian King List, Eridu Genesis, Code of Hammurabi, Emerald Tablets, and more. -The eagle and the serpent, cataclysms during the last ice age, and the influences of the Anunnaki. -Secrets of consciousness, reincarnation, spirituality, and sentient life in the universe.

    Techniques covered include state- and goal-based behavior, inter-agent communication, individual and group steering behaviors, team AI, graph theory, search, path planning and optimization, triggers, scripting, scripted finite state machines, perceptual modeling, goal evaluation, goal arbitration, and fuzzy logic.