Learn You a Haskell for Great Good! introduces programmers familiar with imperative languages (such as C++, Java, or Python) to the unique aspects of functional programming. Packed with jokes, pop culture references, and the author's own hilarious artwork, Learn You a Haskell for Great Good! eases the learning curve of this complex language, and is a perfect starting point for any programmer looking to expand his or her horizons. The well-known web tutorial on which this book is based is widely regarded as the best way for beginners to learn Haskell, and receives over 30,000 unique visitors monthly.

    But sometimes the solutions are not as interesting as the beautiful symmetric patterns that lead to them. Written in a friendly style for a general audience, Fearless Symmetry is the first popular math book to discuss these elegant and mysterious patterns and the ingenious techniques mathematicians use to uncover them.Hidden symmetries were first discovered nearly two hundred years ago by French mathematician �variste Galois. They have been used extensively in the oldest and largest branch of mathematics--number theory--for such diverse applications as acoustics, radar, and codes and ciphers. They have also been employed in the study of Fibonacci numbers and to attack well-known problems such as Fermat's Last Theorem, Pythagorean Triples, and the ever-elusive Riemann Hypothesis. Mathematicians are still devising techniques for teasing out these mysterious patterns, and their uses are limited only by the imagination.The first popular book to address representation theory and reciprocity laws, Fearless Symmetry focuses on how mathematicians solve equations and prove theorems. It discusses rules of math and why they are just as important as those in any games one might play. The book starts with basic properties of integers and permutations and reaches current research in number theory. Along the way, it takes delightful historical and philosophical digressions. Required reading for all math buffs, the book will appeal to anyone curious about popular mathematics and its myriad contributions to everyday life.

    Based on the abstract, general style of mathematical exposition favored by research mathematicians, its goal was to teach students not just to manipulate numbers and formulas, but to grasp the underlying mathematical concepts. The result, at least at first, was a great deal of confusion among teachers, students, and parents. Since then, the negative aspects of "new math" have been eliminated and its positive elements assimilated into classroom instruction.In this charming volume, a noted English mathematician uses humor and anecdote to illuminate the concepts underlying "new math": groups, sets, subsets, topology, Boolean algebra, and more. According to Professor Stewart, an understanding of these concepts offers the best route to grasping the true nature of mathematics, in particular the power, beauty, and utility of pure mathematics. No advanced mathematical background is needed (a smattering of algebra, geometry, and trigonometry is helpful) to follow the author's lucid and thought-provoking discussions of such topics as functions, symmetry, axiomatics, counting, topology, hyperspace, linear algebra, real analysis, probability, computers, applications of modern mathematics, and much more.By the time readers have finished this book, they'll have a much clearer grasp of how modern mathematicians look at figures, functions, and formulas and how a firm grasp of the ideas underlying "new math" leads toward a genuine comprehension of the nature of mathematics itself.

    The first, which describes the force of gravity, is widely known: Einstein's General Theory of Relativity. But the theory that explains everything else--the Standard Model of Elementary Particles--is virtually unknown among the general public.In The Theory of Almost Everything, Robert Oerter shows how what were once thought to be separate forces of nature were combined into a single theory by some of the most brilliant minds of the twentieth century. Rich with accessible analogies and lucid prose, The Theory of Almost Everything celebrates a heretofore unsung achievement in human knowledge--and reveals the sublime structure that underlies the world as we know it.

    In his delightfully down-to-earth style, he explores & explains a mind-boggling future of intelligent robots, extraterrestrial life & its consquences, & other provocative, fascinating quandries of the future we want to see today.

    Enjoy a thrilling intergalactic tour as Andrew Thomas redefines the force of gravity and introduces a brave new view of the universe!

     In 1963, Stephen Hawking was diagnosed with motor neurone disease and given two years to live. More than half a century later, Hawking had made some of the most significant contributions to our understanding of the universe since Albert Einstein. The world’s most famous physics professor, a best-selling author, and a father of three, Stephen lived his life to its fullest. Bridging the world of theoretical physics with the reach of pop culture, Stephen Hawking became an emblem of human determination and intellectual curiosity. Inside you will read about... ✓ Early Life and Terminal Illness ✓ Hawking Radiation and Black Holes ✓ The Hawking Family ✓ A Gambling Man ✓ Late Life and Death And much more!

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Einstein himself said it was “the most valuable theory of my life,” and “of incomparable beauty.” It describes the evolution of the universe, black holes, the behavior of orbiting neutron stars, and why clocks run slower on the surface of the earth than in space. It even suggests the possibility of time travel.And yet when we think of Einstein's breakthrough year, we think instead of 1905, the year of Einstein's Special Theory of Relativity and his equation E=mc2, as his annus mirabilis, even though the Special Theory has a narrower focus.Today the General Theory is overshadowed by these achievements, regarded as 'too difficult' for ordinary mortals to comprehend. In Einstein's Masterwork, John Gribbin puts Einstein's astonishing breakthrough in the context of his life and work, and makes it clear why his greatest year was indeed 1915 and his General Theory his true masterpiece.

    Petr Beckmann holds up this mirror, giving the background of the times when pi made progress -- and also when it did not, because science was being stifled by militarism or religious fanaticism.

    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.

    Now, two of the world's most eminent thinkers -- University of London physicists David Bohm, a former protege of Einstein's and one of the world's most respected quantum physicists, and Stanford neurophysiologist Karl Pribram, one of the architects of our modern understanding of the brain -- believe that the universe itself may be a giant hologram, quite literally a kind of image or construct created, at least in part, by the human mind. This remarkable new way of looking at the universe explains not only many of the unsolved puzzles of physics, but also such mysterious occurrences as telepathy, out-of-body and near death experiences, "lucid" dreams, and even religious and mystical experiences such as feelings of cosmic unity and miraculous healings.

    Widely accepted as the authoritative text and reference on electronic circuit design, both analog and digital, this book revolutionized the teaching of electronics by emphasizing the methods actually used by circuit designers -- a combination of some basic laws, rules of thumb, and a large bag of tricks. The result is a largely nonmathematical treatment that encourages circuit intuition, brainstorming, and simplified calculations of circuit values and performance. The new Art of Electronics retains the feeling of informality and easy access that helped make the first edition so successful and popular. It is an ideal first textbook on electronics for scientists and engineers and an indispensable reference for anyone, professional or amateur, who works with electronic circuits.

    Readers will progress from building a basic physics engine to creating intelligent moving objects and complex systems, setting the foundation for further experiments in generative design. Subjects covered include forces, trigonometry, fractals, cellular automata, self-organization, and genetic algorithms. The book's examples are written in Processing, an open-source language and development environment built on top of the Java programming language. On the book's website (http://www.natureofcode.com), the examples run in the browser via Processing's JavaScript mode.

    Widely recognized as the most comprehensive, accessible and practical basis for scientific computing, this new edition incorporates more than 400 Numerical Recipes routines, many of them new or upgraded. The executable C++ code, now printed in color for easy reading, adopts an object-oriented style particularly suited to scientific applications. The whole book is presented in the informal, easy-to-read style that made earlier editions so popular. Please visit www.nr.com or www.cambridge.org/us/numericalrecipes for more details. More information concerning licenses is available at: www.nr.com/licenses New key features: 2 new chapters, 25 new sections, 25% longer than Second Edition Thorough upgrades throughout the text Over 100 completely new routines and upgrades of many more. New Classification and Inference chapter, including Gaussian mixture models, HMMs, hierarchical clustering, Support Vector MachinesNew Computational Geometry chapter covers KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres New sections include interior point methods for linear programming, Monte Carlo Markov Chains, spectral and pseudospectral methods for PDEs, and many new statistical distributions An expanded treatment of ODEs with completely new routines Plus comprehensive coverage of linear algebra, interpolation, special functions, random numbers, nonlinear sets of equations, optimization, eigensystems, Fourier methods and wavelets, statistical tests, ODEs and PDEs, integral equations, and inverse theory