We don't do a chemical analysis on food we eat.Trust and cooperation are the first problems we had to solve before we could become a social species. In the 21st century, they have become the most important problems we need to solve — again. Our global society has become so large and complex that our traditional trust mechanisms no longer work.Bruce Schneier, world-renowned for his level-headed thinking on security and technology, tackles this complex subject head-on. Society can't function without trust, and yet must function even when people are untrustworthy.Liars and Outliers reaches across academic disciplines to develop an understanding of trust, cooperation, and social stability. From the subtle social cues we use to recognize trustworthy people to the laws that punish the noncompliant, from the way our brains reward our honesty to the bank vaults that keep out the dishonest, keeping people cooperative is a delicate balance of rewards and punishments. It's a series of evolutionary tricks, social pressures, legal mechanisms, and physical barriers.In the absence of personal relationships, we have no choice but to substitute security for trust, compliance for trustworthiness. This progression has enabled society to scale to unprecedented complexity, but has also permitted massive global failures.At the same time, too much cooperation is bad. Without some level of rule-breaking, innovation and social progress become impossible. Society stagnates.Today's problems require new thinking, and Liars and Outliers provides that. It is essential that we learn to think clearly about trust. Our future depends on it.

    This completely updated bestseller was also written with photographers in mind. Author Martin Evening describes features in Lightroom 4 in detail from a photographer’s perspective. As an established commercial and fashion photographer, Martin knows firsthand what photographers need for an efficient workflow. He has also been working with Lightroom from the beginning, monitoring the product’s development and providing valued feedback to Adobe. As a result, Martin knows the software inside and out, from image selection to image editing to image management. In this book you’ll learn how to:• Work efficiently with images shot in the raw or JPEG format • Import photographs with ease and sort them according to your workflow• Create and manage a personal image library• Apply tonal adjustments to multiple images quickly• Integrate Lightroom with Adobe Photoshop• Export images for print or Web as digital contact sheets or personal portfolios• Make the most of new features in Lightroom 4, such as the Camera Raw Process 2012 Basic panel tone controlsPhotographers will find Lightroom 4–and The Adobe Photoshop Lightroom 4 Book–indispensable tools in their digital darkrooms.This book’s companion site, www.thelightroombook.com, offers video tutorials, articles, sample images, and updates from author Martin Evening.“With Martin’s expert guidance, you’ll soon find that you have precisely the tools you need to turn your concentration back where it belongs–on making better pictures!”–George Jardine, digital photography consultant “As a photographer himself, Martin Evening knows what tools photographers need to realize their creative vision. In this book, he shows not only how Adobe Photoshop Lightroom works but also why it will become an essential part of any photographer’s workflow.”–Greg Gorman, photographer

    Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today. Who Should Read This Book: If you’re wondering which lesser known parts in Python you should know about, you’ll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers’ minds in your next code review. If you’ve got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2. If you’ve worked with other programming languages and you want to get up to speed with Python, you’ll pick up the idioms and practical tips you need to become a confident and effective Pythonista. If you want to make Python your own and learn how to write clean and Pythonic code, you’ll discover best practices and little-known tricks to round out your knowledge. What Python Developers Say About The Book: "I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." — Mariatta Wijaya, Python Core Developer"This book makes you write better Python code!" — Bob Belderbos, Software Developer at Oracle"Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." — Ben Felder, Pythonista"It's like having a seasoned tutor explaining, well, tricks!" — Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.

    The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. He includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python. The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.Highlights a Range of Disciplines and ApplicationsDrawing from computer science, statistics, mathematics, and engineering, the multidisciplinary nature of machine learning is underscored by its applicability to areas ranging from finance to biology and medicine to physics and chemistry. Written in an easily accessible style, this book bridges the gaps between disciplines, providing the ideal blend of theory and practical, applicable knowledge."

    From Stephen Levy—the author who made "hackers" a household word—comes this account of a revolution that is already affecting every citizen in the twenty-first century. Crypto tells the inside story of how a group of "crypto rebels"—nerds and visionaries turned freedom fighters—teamed up with corporate interests to beat Big Brother and ensure our privacy on the Internet. Levy's history of one of the most controversial and important topics of the digital age reads like the best futuristic fiction.

    You’ll learn about authenticated encryption, secure randomness, hash functions, block ciphers, and public-key techniques such as RSA and elliptic curve cryptography.You’ll also learn: - Key concepts in cryptography, such as computational security, attacker models, and forward secrecy - The strengths and limitations of the TLS protocol behind HTTPS secure websites - Quantum computation and post-quantum cryptography - About various vulnerabilities by examining numerous code examples and use cases - How to choose the best algorithm or protocol and ask vendors the right questionsEach chapter includes a discussion of common implementation mistakes using real-world examples and details what could go wrong and how to avoid these pitfalls. Whether you’re a seasoned practitioner or a beginner looking to dive into the field, Serious Cryptography will provide a complete survey of modern encryption and its applications.

    Understanding Computation explains theoretical computer science in a context you’ll recognize, helping you appreciate why these ideas matter and how they can inform your day-to-day programming.Rather than use mathematical notation or an unfamiliar academic programming language like Haskell or Lisp, this book uses Ruby in a reductionist manner to present formal semantics, automata theory, and functional programming with the lambda calculus. It’s ideal for programmers versed in modern languages, with little or no formal training in computer science.* Understand fundamental computing concepts, such as Turing completeness in languages* Discover how programs use dynamic semantics to communicate ideas to machines* Explore what a computer can do when reduced to its bare essentials* Learn how universal Turing machines led to today’s general-purpose computers* Perform complex calculations, using simple languages and cellular automata* Determine which programming language features are essential for computation* Examine how halting and self-referencing make some computing problems unsolvable* Analyze programs by using abstract interpretation and type systems

    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

    

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    It is a book I recommend." --Scott Guthrie, Corporate Vice President, .NET Developer Platform, Microsoft Corporation "A must-read for a concise but thorough examination of the parallel programming features in the .NET Framework 4." --Stephen Toub, Parallel Computing Platform Program Manager, Microsoft "This wonderful book is a great reference for developers of all levels." -- Chris Burrows, C# Compiler Team, Microsoft When you have questions about how to use C# 4.0 or the .NET CLR, this highly acclaimed bestseller has precisely the answers you need. Uniquely organized around concepts and use cases, this fourth edition includes in-depth coverage of new C# topics such as parallel programming, code contracts, dynamic programming, security, and COM interoperability. You'll also find updated information on LINQ, including examples that work with both LINQ to SQL and Entity Framework. This book has all the essential details to keep you on track with C# 4.0. Get up to speed on C# language basics, including syntax, types, and variables Explore advanced topics such as unsafe code and preprocessor directives Learn C# 4.0 features such as dynamic binding, type parameter variance, and optional and named parameters Work with .NET 4's rich set of features for parallel programming, code contracts, and the code security model Learn .NET topics, including XML, collections, I/O and networking, memory management, reflection, attributes, security, and native interoperability

    It is through an understanding of service design that truly service-oriented solution logic can be created in support of achieving the strategic goals associated with SOA and service-oriented computing. Bestselling SOA author Thomas Erl guides you through a comprehensive, insightful, and visually rich exploration of the service-orientation design paradigm, revealing exactly how services should and should not be designed for real-world SOA. concise introduction to SOA and service-oriented computing concepts and benefits* A thorough exploration of the service-orientation design paradigm as represented by eight specific design principles* A comparison of service-oriented and object-oriented concepts and principles and a clear definition of what qualifies as service-oriented logic* Detailed coverage of four different forms of service-related design granularity* An exhaustive examination of service contracts, with an emphasis on standardization, abstraction, and the utilization of WS-Policy, XML Schema, and WSDL definitions* A comprehensive study of various forms of service-related coupling with an emphasis on the requirements to attaining a suitable level of loose coupling.* achieve truly agnostic and reusable service logic* Techniques for maximizing service reliability, scalability, and performance by instilling high levels of autonomy and emphasizing stateless design* Approaches for positioning services as highly discoverable and interpretable enterprise resources* Unprecedented coverage of how to design services for participation in complex compositions* The definition of concrete links between each design principle and the strategic goals and benefits of SOA and service-oriented computing* Numerous cross-references to key design patterns documented separately in SOA: Design Patterns www.soabooks.com supplements this book with a variety of resources, including content updates, corrections, and sample chapters from other books. www.soaspecs.com provides further support by establishing a descriptive portal to industry specifications referenced in all of the series titles. www.soaglossary.com establishes a master glossary for all SOA titles in this series. www.prenhallprofessional.comwww.soabo... Foreword Chapter 1: OverviewChapter 2: Case Study Background Pa

    Gödel received public recognition of his work in 1951 when he was awarded the first Albert Einstein Award for achievement in the natural sciences--perhaps the highest award of its kind in the United States. The award committee described his work in mathematical logic as "one of the greatest contributions to the sciences in recent times."However, few mathematicians of the time were equipped to understand the young scholar's complex proof. Ernest Nagel and James Newman provide a readable and accessible explanation to both scholars and non-specialists of the main ideas and broad implications of Gödel's discovery. It offers every educated person with a taste for logic and philosophy the chance to understand a previously difficult and inaccessible subject.New York University Press is proud to publish this special edition of one of its bestselling books. With a new introduction by Douglas R. Hofstadter, this book will appeal students, scholars, and professionals in the fields of mathematics, computer science, logic and philosophy, and science.

    In addition to giving a strong foundation in the language itself, Lubanovic shows how to use it for a range of applications in business, science, and the arts, drawing on the rich collection of open source packages developed by Python fans.It's impressive how many commercial and production-critical programs are written now in Python. Developed to be easy to read and maintain, it has proven a boon to anyone who wants applications that are quick to write but robust and able to remain in production for the long haul.This book focuses on the current version of Python, 3.x, while including sidebars about important differences with 2.x for readers who may have to deal with programs in that version.

    The text offers a flexible organization, enabling instructors to adapt the book to their particular courses. The book is both complete and careful, and it continues to maintain its emphasis on algorithms and applications. Excellent exercise sets allow students to perfect skills as they practice. This new edition continues to feature numerous computer science applications-making this the ideal text for preparing students for advanced study.