The OpenGL Programming Guide provides definitive and comprehensive information on OpenGL and the OpenGL Utility Library. It is far and away the most important book on OpenGL, and is commonly referred to by programmers simply as the Red book. Last summer the OpenGL Architectural Review Board (ARB) announced the release of the version 2.0 standard, incorporating the OpenGL Shader Language (GLSL) officially into the spec. This is the biggest change in OpenGL since its inception. This new edition will provide basic information about GLSL itself, as well as all the other changes to the 1.5 and 1.0 versions. the official, comprehensive guide to GLSL itself. A few years ago, pundits were predicting the imminent demise of OpenGL. Far from expiring, however, OpenGL has had a resurgence in the last couple years, and has solidified its position as the defacto standard for high-quality computer graphics. This book remains the necessary guide for any developer doing graphics programming. The sample source code in the book will be available on the book's web site.

    Joining the professional web designers and programmers are new audiences who need to know a little bit of code at work (update a content management system or e-commerce store) and those who want to make their personal blogs more attractive. Many books teaching HTML and CSS are dry and only written for those who want to become programmers, which is why this book takes an entirely new approach. • Introduces HTML and CSS in a way that makes them accessible to everyone—hobbyists, students, and professionals—and it’s full-color throughout • Utilizes information graphics and lifestyle photography to explain the topics in a simple way that is engaging • Boasts a unique structure that allows you to progress through the chapters from beginning to end or just dip into topics of particular interest at your leisureThis educational book is one that you will enjoy picking up, reading, then referring back to. It will make you wish other technical topics were presented in such a simple, attractive and engaging way!

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

    This book teaches basic Artificial Intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, Nelder Mead, and linear regression. These are not just foundational algorithms for the rest of the series, but are very useful in their own right. The book explains all algorithms using actual numeric calculations that you can perform yourself. Artificial Intelligence for Humans is a book series meant to teach AI to those without an extensive mathematical background. The reader needs only a knowledge of basic college algebra or computer programming—anything more complicated than that is thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, R, Python and C. Other languages planned.

    In barely six years, a small group of young, ambitious programmers in Silicon Valley built an $11.5 billion business out of the ashes of a failed podcasting company. Today Twitter boasts more than 200 million active users and has affected business, politics, media, and other fields in innumerable ways. Now Nick Bilton of the New York Times takes readers behind the scenes with a narrative that shows what happened inside Twitter as it grew at exponential speeds. This is a tale of betrayed friendships and high-stakes power struggles as the four founders—Biz Stone, Evan Williams, Jack Dorsey, and Noah Glass—went from everyday engineers to wealthy celebrities, featured on magazine covers, Oprah, The Daily Show, and Time’s list of the world’s most influential people. Bilton’s exclusive access and exhaustive investigative reporting—drawing on hundreds of sources, documents, and internal e-mails—have enabled him to write an intimate portrait of fame, influence, and power. He also captures the zeitgeist and global influence of Twitter, which has been used to help overthrow governments in the Middle East and disrupt the very fabric of the way people communicate.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

    Then he went back and built the machine. It worked. The whole world changed. Why don’t we know the name of John Atanasoff as well as we know those of Alan Turing and John von Neumann? Because he never patented the device, and because the developers of the far-better-known ENIAC almost certainly stole critical ideas from him. But in 1973 a court declared that the patent on that Sperry Rand device was invalid, opening the intellectual property gates to the computer revolution. Jane Smiley tells the quintessentially American story of the child of immigrants John Atanasoff with technical clarity and narrative drive, making the race to develop digital computing as gripping as a real-life techno-thriller.

    The latter half of our century has seen its own Renaissance - informations technology has changed irrevocable the way we live, work, and think about the world. We are fortunate, therefore, that the authors of Out of Their Minds have been able to talk so candidly with the founders of computer science. In Out of their Minds, readers will hear the Newtons and Euclids of the computer age as they talk about their discoveries in information technology that have changed forever the way we live, work, and think about the world. Based on interviews by freelance writer Cathy Lazere and the expertise of computer scientist Dennis Shasha, Out of their Minds introduces readers to fifteen of the planet's foremost computer scientists, including eight winners of the Turing Award, computing's Nobel Prize. The scientists reveal themselves in fascinating anecdotes about their early inspirations and influences, their contributions to computer science, and their thoughts on its explosive future. These are the programmers whose work

    With this book, you'll get a candid and insightful look at how software is constructed and maintained by some of the world's leading practitioners.Titus Winters, Tom Manshreck, and Hyrum K. Wright, software engineers and a technical writer at Google, reframe how software engineering is practiced and taught: from an emphasis on programming to an emphasis on software engineering, which roughly translates to programming over time.You'll learn:Fundamental differences between software engineering and programmingHow an organization effectively manages a living codebase and efficiently responds to inevitable changeWhy culture (and recognizing it) is important, and how processes, practices, and tools come into play

    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.

    WikiLeaks brought to light a new form of whistleblowing, using powerful cryptographic code to hide leakers’ identities while they spill the private data of government agencies and corporations. But that technology has been evolving for decades in the hands of hackers and radical activists, from the libertarian enclaves of Northern California to Berlin to the Balkans. And the secret-killing machine continues to evolve beyond WikiLeaks, as a movement of hacktivists aims to obliterate the world’s institutional secrecy.This is the story of the code and the characters—idealists, anarchists, extremists—who are transforming the next generation’s notion of what activism can be.With unrivaled access to such major players as Julian Assange, Daniel Domscheit-Berg, and WikiLeaks’ shadowy engineer known as the Architect, never before interviewed, reporter Andy Greenberg unveils the world of politically-motivated hackers—who they are and how they operate.

    We nevertheless muddle through even in the absence of theories of how to act. But how do we do it?In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. The key is “probably approximately correct” algorithms, a concept Valiant developed to explain how effective behavior can be learned. The model shows that pragmatically coping with a problem can provide a satisfactory solution in the absence of any theory of the problem. After all, finding a mate does not require a theory of mating. Valiant’s theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.Offering a powerful and elegant model that encompasses life’s complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence.

    Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization’s massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It’s a big, big data world out there – let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

    Ada's life spanned the years 1815 to 1852, during which the newly introduced rail lines and telegraph access made the power of technology a reality in people's lives. The Romantic movement was the backlash against those who would attempt to apply "scientific" thinking to every aspect of the human experience. As one of the Romantic movement's greatest prophets, Lord Byron's excessive indulgence of various illicit desires (one being particularly dangerous) led him to marry a woman who deluded herself into believing she could save him. Ada's mother, Annabella, was the dominant force in her life -- a self-righteous and self-serving woman who embraced the new virtues of rationality.The marriage lasted barely long enough for Annabella to become pregnant, and she spent the rest of her life justifying the infamous separation from her celebrity husband. Annabella barred Byron from any contact with his daughter and put Ada on a strict regimen of moral and mathematical study to suppress any Byronic tendencies Ada may have inherited. To the public eye, Ada was a curiosity. Put upon in an entirely modern way, Ada was famous from the day she was born. Although Ada took up science with enthusiasm, her Byronic eccentricities and passions were not extinguished by logic. Like her father, Ada looked to marriage to save her, but her husband, the future Earl of Lovelace, was not able to control her in the end. As an adult, Ada set out to find her mission, which she hoped would combine her two halves, and prove that the product of science and poetry would produce genius, not a monstrosity. Her work with Babbage was one attempt at a "poetical science" requiring imagination and rigor. She also indulged in many of the other popular ideas of the day, such as phrenology and mesmerism, with a more discerning eye than most. At the end of her life, she turned to the new work being done with that mysterious force, electricity, in the hopes of finding a molecular basis in the human nervous system to explain emotions. She was plagued by this time with both physical and mental disorders, and so also hoped to find some personal salvation in this quest. But her Byronic nature was getting stronger in the form of an affair and gambling addiction (there is an interesting speculation that she tried to develop a mathematical formula to beat the odds), and she finally succumbed to illness. In the end she requested to be buried next to the father she never knew in life. The Bride of Science is a wonderful portrait of the struggle between reason and passion. --Laura Wood, Science & Nature Editor