What You Will Learn Design and implement a series of server-side JavaScript patterns so you understand why and when to apply them in different use case scenarios Understand the fundamental Node.js components and use them to their full potential Untangle your modules by organizing and connecting them coherently Reuse well-known solutions to circumvent common design and coding issues Deal with asynchronous code with comfort and ease Identify and prevent common problems, programming errors, and anti-patterns In Detail Node.js is a massively popular software platform that lets you use JavaScript to easily create scalable server-side applications. It allows you to create efficient code, enabling a more sustainable way of writing software made of only one language across the full stack, along with extreme levels of reusability, pragmatism, simplicity, and collaboration. Node.js is revolutionizing the web and the way people and companies create their software.In this book, we will take you on a journey across various ideas and components, and the challenges you would commonly encounter while designing and developing software using the Node.js platform. You will also discover the "Node.js way" of dealing with design and coding decisions.The book kicks off by exploring the fundamental principles and components that define the platform. It then shows you how to master asynchronous programming and how to design elegant and reusable components using well-known patterns and techniques. The book rounds off by teaching you the various approaches to scale, distribute, and integrate your Node.js application.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    From Mary, Queen of Scots, trapped by her own code, to the Navajo Code Talkers who helped the Allies win World War II, to the incredible (and incredibly simple) logisitical breakthrough that made Internet commerce secure, The Code Book tells the story of the most powerful intellectual weapon ever known: secrecy.Throughout the text are clear technical and mathematical explanations, and portraits of the remarkable personalities who wrote and broke the world’s most difficult codes. Accessible, compelling, and remarkably far-reaching, this book will forever alter your view of history and what drives it. It will also make you wonder how private that e-mail you just sent really is.

    Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations.You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tablesStudy abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machinesGet starter code and solutions to help you re-implement and extend original experiments in complexityExplore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topicsExamine case studies of complex systems submitted by students and readers

    But instead of spending hours and hours trying to develop your own answers, now you can find out how the pros do it! Game Programming Gems is a hands-on, comprehensive resource packed with a variety of game programming algorithms written by experts from the game industry and edited by Mark DeLoura, former software engineering lead for Nintendo of America, Inc. and now the newly appointed editor-in-chief of Game Developer magazine. From animation and artificial intelligence to Z-buffering, lighting calculations, weather effects, curved surfaces, mutliple layer Internet gaming, to music and sound effects, all of the major techniques needed to develop a competitive game engine are covered. Game Programming Gems is written in a style accessible to individuals with a range of expertise levels. All of the source code for each algorithm is included and can be used by advanced programmers immediately. For aspiring programmers, there is a detailed tutorial to work through before attempting the code, and suggestions for possible modifications and optimizations are included as well.

    In Sound Unbound, Rhythm Science author Paul Miller aka DJ Spooky that Subliminal Kid asks artists to describe their work and compositional strategies in their own words. These are reports from the front lines on the role of sound and digital media in an information-based society. The topics are as diverse as the contributors: composer Steve Reich offers a memoir of his life with technology, from tape loops to video opera; Miller himself considers sampling and civilization; novelist Jonathan Lethem writes about appropriation and plagiarism; science fiction writer Bruce Sterling looks at dead media; Ron Eglash examines racial signifiers in electrical engineering; media activist Naeem Mohaiemen explores the influence of Islam on hip hop; rapper Chuck D contributes "Three Pieces"; musician Brian Eno explores the sound and history of bells; Hans Ulrich Obrist and Philippe Parreno interview composer-conductor Pierre Boulez; and much more. "Press 'play, '" Miller writes, "and this anthology says 'here goes.'"The groundbreaking music that accompanies the book features Nam Jun Paik, the Dada Movement, John Cage, Sonic Youth, and many other examples of avant-garde music. Most of this content comes from the archives of Sub Rosa, a legendary record label that has been the benchmark for archival sounds since the beginnings of electronic music. To receive these free music files, readers may send an email to the address listed in the book.ContributorsDavid Allenby, Pierre Boulez, Catherine Corman, Chuck D, Erik Davis, Scott De Lahunta, Manuel DeLanda, Cory Doctorow, Eveline Domnitch, Frances Dyson, Ron Eglash, Brian Eno, Dmitry Gelfand, Dick Hebdige, Lee Hirsch, Vijay Iyer, Ken Jordan, Douglas Kahn, Daphne Keller, Beryl Korot, Jaron Lanier, Joseph Lanza, Jonathan Lethem, Carlo McCormick, Paul D. Miller aka DJ Spooky that Subliminal Kid, Moby, Naeem Mohaiemen, Alondra Nelson, Keith and Mendi Obadike, Hans Ulrich Obrist, Pauline Oliveros, Philippe Parreno, Ibrahim Quaraishi, Steve Reich, Simon Reynolds, Scanner aka Robin Rimbaud, Nadine Robinson, Daniel Bernard Roumain (DBR), Alex Steinweiss, Bruce Sterling, Lucy Walker, Saul Williams, Jeff E. Winner

    This book is neither a step-by-step tutorial nor a reference book. Instead, our goal is to bring a diverse set of software engineering topics together into a single narrative, help readers understand the most important ideas through concrete examples and a learn-by-doing approach, and teach readers enough about each topic to get them started in the field. Courseware for doing the work in the book is available as a virtual machine image that can be downloaded or deployed in the cloud. A free MOOC (massively open online course) at saas-class.org follows the book's content and adds programming assignments and quizzes. See http://saasbook.info for details.

    With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

     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.

    You’ll learn principles and practices for crafting games that generate emotionally charged experiences—a combination of elegant game mechanics, compelling fiction, and pace that fully immerses players.In clear and approachable prose, design pro Tynan Sylvester also looks at the day-to-day process necessary to keep your project on track, including how to work with a team, and how to avoid creative dead ends. Packed with examples, this book will change your perception of game design.Create game mechanics to trigger a range of emotions and provide a variety of playExplore several options for combining narrative with interactivityBuild interactions that let multiplayer gamers get into each other’s headsMotivate players through rewards that align with the rest of the gameEstablish a metaphor vocabulary to help players learn which design aspects are game mechanicsPlan, test, and analyze your design through iteration rather than deciding everything up frontLearn how your game’s market positioning will affect your design

    Learn how to design beautiful user interfaces by yourself using specific tactics explained from a developer's point-of-view.

    It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

    And this may sound weirdly obvious, but every single one of those pieces of software was written by a programmer. Programmers are thus among the most quietly influential people on the planet. As we live in a world made of software, they're the architects. The decisions they make guide our behavior. When they make something newly easy to do, we do a lot more of it. If they make it hard or impossible to do something, we do less of it.If we want to understand how today's world works, we ought to understand something about coders. Who exactly are the people that are building today's world? What makes them tick? What type of personality is drawn to writing software? And perhaps most interestingly -- what does it do to them?One of the first pieces of coding a newbie learns is the program to make the computer say "Hello, world!" Like that piece of code, Clive Thompson's book is a delightful place to begin to understand this vocation, which is both a profession and a way of life, and which essentially didn't exist little more than a generation ago, but now is considered just about the only safe bet we can make about what the future holds. Thompson takes us close to some of the great coders of our time, and unpacks the surprising history of the field, beginning with the first great coders, who were women. Ironically, if we're going to traffic in stereotypes, women are arguably "naturally" better at coding than men, but they were written out of the history, and shoved out of the seats, for reasons that are illuminating. Now programming is indeed, if not a pure brotopia, at least an awfully homogenous community, which attracts people from a very narrow band of backgrounds and personality types. As Thompson learns, the consequences of that are significant - not least being a fetish for disruption at scale that doesn't leave much time for pondering larger moral issues of collateral damage. At the same time, coding is a marvelous new art form that has improved the world in innumerable ways, and Thompson reckons deeply, as no one before him has, with what great coding in fact looks like, who creates it, and where they come from. To get as close to his subject has he can, he picks up the thread of his own long-abandoned coding practice, and tries his mightiest to up his game, with some surprising results.More and more, any serious engagement with the world demands an engagement with code and its consequences, and to understand code, we must understand coders. In that regard, Clive Thompson's Hello, World! is a marvelous and delightful master class.