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 can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    Who invented zero? Why are there 60 seconds in a minute? Can a butterfly's wings really cause a storm on the far side of the world? In 50 concise essays, Professor Tony Crilly explains the mathematical concepts that allow use to understand and shape the world around us.

    Are you thinking about getting into triathlon or attempting your first race? Maybe you’re curious about this whole “Triathlon” thing and want to know if its right for you?If you've ever thought about doing a triathlon, you’re in the right place . Triathlon: the Beginners Guide Will Be Your Trusted Guide Triathlon can be confusing.  Let me help you get started. Don’t be intimidated by skinny 20-somethings squeezed into lycra. Don’t rush into dangerous amounts of joint-pounding training; risking your health. Don’t be fooled into buying tons of expensive and unnecessary equipment. The Beginners Guide will act as your road-map to Triathlon success It covers every aspect of your triathlon, including: which Triathlon distance is right for you how to swim and get over the fear of swimming in open-water, away from the safety and familiarity of your local pool. becoming a fast (and safe) cyclist, without spending thousands of dollars on a professional-grade bike how to run after you’ve just finished an intense bike ride what to look for in a triathlon training plan, and how to tell if you should tear yours up on the spot what you need to eat and drink; before, during and after your race how to put it all together in the intense “transition area” and how to survive race day nerves and the complex logistics of a triathlon race site. I’ll Also Reveal these Nuggets of Triathlon Gold; Earned from Over 25 Years of Triathlon the same “Six Periods of Training” I use with my $1000 per month one-on-one students the simple truth about structuring your Triathlon training . . . no math formula or science PhD required why “standard” advice about open-water swimming will leave you gasping for air while others swim over the top of you the most powerful cure for fear of swimming ever known . . . and why it’s easier to fix than you’ve ever thought possible the single little-known secret of triathlon training to dramatically reduce your risk of injury . . . by up to as much as 90% the only list you’ll ever need for all your Triathlon planning why most Triathlon coaches are 100% wrong in the way they approach race day how to avoid the embarrassing mistakes even veteran triathletes make on race day Start Your Triathlon Journey Today Triathlons the Beginners Guide is everything a new triathl

    His breaking of the German U-boat Enigma cipher in World War II ensured Allied-American control of the Atlantic. But Turing's vision went far beyond the desperate wartime struggle. Already in the 1930s he had defined the concept of the universal machine, which underpins the computer revolution. In 1945 he was a pioneer of electronic computer design. But Turing's true goal was the scientific understanding of the mind, brought out in the drama and wit of the famous "Turing test" for machine intelligence and in his prophecy for the twenty-first century.Drawn in to the cockpit of world events and the forefront of technological innovation, Alan Turing was also an innocent and unpretentious gay man trying to live in a society that criminalized him. In 1952 he revealed his homosexuality and was forced to participate in a humiliating treatment program, and was ever after regarded as a security risk. His suicide in 1954 remains one of the many enigmas in an astonishing life story.

    This book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, more. Includes exercises. 1976 edition.

    This concept is at the root of the computational worldview, which basically says that very complex systems — the world we live in — have their beginnings in simple mathematical equations. We've lately come to understand that such an algorithm is only the start of a never-ending story — the real action occurs in the unfolding consequences of the rules. The chip-in-a-box computers so popular in our time have acted as a kind of microscope, letting us see into the secret machinery of the world. In Lifebox, Rucker uses whimsical drawings, fables, and humor to demonstrate that everything is a computation — that thoughts, computations, and physical processes are all the same. Rucker discusses the linguistic and computational advances that make this kind of "digital philosophy" possible, and explains how, like every great new principle, the computational world view contains the seeds of a next step.

    This book is designed to give the reader insight into the power and beauty that accrues from a rich interplay between different areas of mathematics. The book carefully develops the theory of different algebraic structures, beginning from basic definitions to some in-depth results, using numerous examples and exercises to aid the reader's understanding. In this way, readers gain an appreciation for how mathematical structures and their interplay lead to powerful results and insights in a number of different settings. * The emphasis throughout has been to motivate the introduction and development of important algebraic concepts using as many examples as possible.

    Covers textual and linguistic matters; mathematical analyses of Euclid's ideas; commentators; refutations, supports, extrapolations, reinterpretations and historical notes. Vol. 1 includes Introduction, Books 1-2: Triangles, rectangles.

     In MATH WITH BAD DRAWINGS, Ben Orlin answers math's three big questions: Why do I need to learn this? When am I ever going to use it? Why is it so hard? The answers come in various forms-cartoons, drawings, jokes, and the stories and insights of an empathetic teacher who believes that math should belong to everyone.Eschewing the tired old curriculum that begins in the wading pool of addition and subtraction and progresses to the shark infested waters of calculus (AKA the Great Weed Out Course), Orlin instead shows us how to think like a mathematician by teaching us a new game of Tic-Tac-Toe, how to understand an economic crisis by rolling a pair of dice, and the mathematical reason why you should never buy a second lottery ticket. Every example in the book is illustrated with his trademark "bad drawings," which convey both his humor and his message with perfect pitch and clarity. Organized by unconventional but compelling topics such as "Statistics: The Fine Art of Honest Lying," "Design: The Geometry of Stuff That Works," and "Probability: The Mathematics of Maybe," MATH WITH BAD DRAWINGS is a perfect read for fans of illustrated popular science.

    And then we wonder why software is notorious for being delivered late and full of bugs, while other engineers routinely deliver finished bridges, automobiles, electrical appliances, etc., on time and with only minor defects. This book sets out to redress this imbalance. Members of my advanced development team at Adobe who took the course based on the same material all benefited greatly from the time invested. It may appear as a highly technical text intended only for computer scientists, but it should be required reading for all practicing software engineers." --Martin Newell, Adobe Fellow"The book contains some of the most beautiful code I have ever seen." --Bjarne Stroustrup, Designer of C++"I am happy to see the content of Alex's course, the development and teaching of which I strongly supported as the CTO of Silicon Graphics, now available to all programmers in this elegant little book." --Forest Baskett, General Partner, New Enterprise Associates"Paul's patience and architectural experience helped to organize Alex's mathematical approach into a tightly-structured edifice--an impressive feat!" --Robert W. Taylor, Founder of Xerox PARC CSL and DEC Systems Research Center Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.This is not an easy book. Nor is it a compilation of tips and tricks for incremental improvements in your programming skills. The book's value is more fundamental and, ultimately, more critical for insight into programming. To benefit fully, you will need to work through it from beginning to end, reading the code, proving the lemmas, and doing the exercises. When finished, you will see how the application of the deductive method to your programs assures that your system's software components will work together and behave as they must.The book presents a number of algorithms and requirements for types on which they are defined. The code for these descriptions--also available on the Web--is written in a small subset of C++ meant to be accessible to any experienced programmer. This subset is defined in a special language appendix coauthored by Sean Parent and Bjarne Stroustrup.Whether you are a software developer, or any other professional for whom programming is an important activity, or a committed student, you will come to understand what the book's experienced authors have been teaching and demonstrating for years--that mathematics is good for programming, and that theory is good for practice.

    In fact, nearly three times as many Labs were registered in 2002 than any other breed. The Everything Labrador Retriever Book is the perfect introduction to America’s most popular pet. Written by dog expert Kim Campbell Thornton, The Everything Labrador Retriever Book is packed with professional, breed-specific advice that helps readers raise, care for, and train their Lab safely and successfully. Packed full of photos showing Labs in action, The Everything Labrador Retriever Book is perfect for new and seasoned dog owners!

    Rocketed to popularity by the 2003 bestseller Moneyball and the film of the same name, the use of sabermetrics to analyze player performance has appeared to be a David to the Goliath of systemically advantaged richer teams that could be toppled only by creative statistical analysis. The story has been so compelling that, over the past decade, team after team has integrated statistical analysis into its front office. But how accurately can crunching numbers quantify a player's ability? Do sabermetrics truly level the playing field for financially disadvantaged teams? How much of the baseball analytic trend is fad and how much fact?The Sabermetric Revolution sets the record straight on the role of analytics in baseball. Former Mets sabermetrician Benjamin Baumer and leading sports economist Andrew Zimbalist correct common misinterpretations and develop new methods to assess the effectiveness of sabermetrics on team performance. Tracing the growth of front office dependence on sabermetrics and the breadth of its use today, they explore how Major League Baseball and the field of sports analytics have changed since the 2002 season. Their conclusion is optimistic, but the authors also caution that sabermetric insights will be more difficult to come by in the future. The Sabermetric Revolution offers more than a fascinating case study of the use of statistics by general managers and front office executives: for fans and fantasy leagues, this book will provide an accessible primer on the real math behind moneyball as well as new insight into the changing business of baseball.