It is designed as a reference for students in the physical sciences and engineering.

    Their accomplishments are unparalleled, with countless World Series of Poker and World Poker Tour championships to their names and well in excess of $100 million in winnings in private games. Now, this group of poker legends has banded together to create The Full Tilt Poker Strategy Guide, which will stand as an instant classic of the genre and is sure to become the industry standard.

    The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks, Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function.This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business.

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    Windows Presentation Foundation (WPF) is the recommended technology for creating Windows user interfaces, giving you the power to create richer and more compelling applications than you dreamed possible. Whether you want to develop traditional user interfaces or integrate 3D graphics, audio/video, animation, dynamic skinning, multi-touch, rich document support, speech recognition, or more, WPF enables you to do so in a seamless, resolution-independent manner. WPF 4 Unleashed is the authoritative book that covers it all, in a practical and approachable fashion, authored by WPF guru and Microsoft developer Adam Nathan. Covers everything you need to know about Extensible Application Markup Language (XAML) Examines the WPF feature areas in incredible depth: controls, layout, resources, data binding, styling, graphics, animation, and more Highlights the latest features, such as multi-touch, text rendering improvements, XAML language enhancements, new controls, the Visual State Manager, easing functions, and much more Delves into topics that aren't covered by most books: 3D, speech, audio/video, documents, effects Shows how to create popular UI elements, such as Galleries, ScreenTips, and more Demonstrates how to create sophisticated UI mechanisms, such as Visual Studio-like collapsible/dockable panes Explains how to create first-class custom controls for WPF Demonstrates how to create hybrid WPF software that leverages Windows Forms, DirectX, ActiveX, or other non-WPF technologies Explains how to exploit new Windows 7 features, such as Jump Lists and taskbar customizations

    

    Inside: Logic Resource CD-ROM

    Numerous examples are provided to reinforce the concepts and relevant case studies illustrate the concepts and mechanisms described.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    has been involved in some of the most sensational cases of our time. Now Grave Secrets takes you on a personal tour behind the scenes of these notorious incidents-touching on cases as varied as O.J. Simpson, Vincent Foster, and even the much-publicized "Alien Autopsy." Through shocking eyewitness testimony and crucial findings of facts, Cyril Wecht's expert opinion is sure to enlighten and fascinate true crime fans everywhere! � Newly updated for paperback! br� GRAVE SECRETS provides controversial and stunning revelations, such as: br� Evidence pointing to a second killer in the O.J. Simpson murder case br� Whether or not White House counselVincent Foster really committed suicide br� Why the secrets surrounding the "Alien Autopsy" continue to elude the public br� Cyril Wecht has provided expert commentary on "20/20," "Nightline," "The Larry King Show," and news specials with Dan Rather, Geraldo Rivera, Tom Snyder, and Maury Povich br� Cyril Wecht is the former president of both the American Academy of Forensic Science and the American College of Legal Medicine br� Contains 8 pages of compelling photos

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    Notions like denumerability, modal scope distinction, Bayesian conditionalization, and logical completeness are usually only elucidated deep within difficultspecialist texts. By offering simple explanations that by-pass much irrelevant and boring detail, Philosophical Devices is able to cover a wealth of material that is normally only available to specialists.The book contains four sections, each of three chapters. The first section is about sets and numbers, starting with the membership relation and ending with the generalized continuum hypothesis. The second is about analyticity, a prioricity, and necessity. The third is about probability, outliningthe difference between objective and subjective probability and exploring aspects of conditionalization and correlation. The fourth deals with metalogic, focusing on the contrast between syntax and semantics, and finishing with a sketch of Godel's theorem.Philosophical Devices will be useful for university students who have got past the foothills of philosophy and are starting to read more widely, but it does not assume any prior expertise. All the issues discussed are intrinsically interesting, and often downright fascinating. It can be read withpleasure and profit by anybody who is curious about the technical infrastructure of contemporary philosophy.

    A basic idea that proved elusive for hundreds of years and bent the minds of the greatest thinkers in the world, the algorithm is what made the modern world possible. Without the algorithm, there would have been no computer, no Internet, no virtual reality, no e-mail, or any other technological advance that we rely on every day.In The Advent of the Algorithm, David Berlinski combines science, history, and math to explain and explore the intriguing story of how the algorithm was finally discovered by a succession of mathematicians and logicians, and how this paved the way for the digital age. Beginning with Leibniz and culminating in the middle of the twentieth century with the groundbreaking work of Gödel and Turing, The Advent of the Algorithm is an epic tale told with clarity and imaginative brilliance.

    Unfortunately, most programmers frequently have a limited understanding of these essential mathematics and physics concepts. MATHEMATICS AND PHYSICS FOR PROGRAMMERS, THIRD EDITION provides a simple but thorough grounding in the mathematics and physics topics that programmers require to write algorithms and programs using a non-language-specific approach. Applications and examples from game programming are included throughout, and exercises follow each chapter for additional practice. The book's companion website provides sample code illustrating the mathematical and physics topics discussed in the book.

    A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow.