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

    You'll learn pragmatic ways of approaching the development process and your personal coding techniques. You'll learn about your own attitudes, issues with working on a team, and how to best manage your learning, all in an iterative, incremental, agile style. You'll see how to apply each practice, and what benefits you can expect. Bottom line: This book will make you a better developer.

    Along the way, we encounter black holes, turtles, snakes, dragons, axe-sharpening, and yak-shaving—and take a guided tour through the theories and methods, both brilliant and misguided, that litter the history of software development, from the famous ‘mythical man-month’ to Extreme Programming. Not just for technophiles but for anyone captivated by the drama of invention, Dreaming in Code offers a window into both the information age and the workings of the human mind.

    This book attempts to capture the engineering wisdom and design philosophy of the UNIX, Linux, and Open Source software development community as it has evolved over the past three decades, and as it is applied today by the most experienced programmers. Eric Raymond offers the next generation of hackers the unique opportunity to learn the connection between UNIX philosophy and practice through careful case studies of the very best UNIX/Linux programs.

    Written for 11- to 15-year-olds and assuming no prior computing knowledge, this book uses the wildly successful, low-cost, credit-card-sized Raspberry Pi computer to explain fundamental computing concepts. Young people will enjoy going through the book's nine fun projects while they learn basic programming and system administration skills, starting with the very basics of how to plug in the board and turn it on. Each project includes a lively and informative video to reinforce the lessons. It's perfect for young, eager self-learners—your kids can jump in, set up their Raspberry Pi, and go through the lessons on their own. Written by Carrie Anne Philbin, a high school teacher of computing who advises the U.K. government on the revised ICT Curriculum Teaches 11- to 15-year-olds programming and system administration skills using Raspberry Pi Features 9 fun projects accompanied by lively and helpful videos Raspberry Pi is a $35/£25 credit-card-sized computer created by the non-profit Raspberry Pi Foundation; over a million have been sold Help your children have fun and learn computing skills at the same time with Adventures in Raspberry Pi.

    This book will help the C programmer reach new heights as a professional. Organized to make it easy for the reader to scan to sections that are relevant to their immediate needs.

    But they've often been hidden in plain sight, their inventions and contributions touching our lives in ways we don't even realize.Author Claire L. Evans finally gives these unsung female heroes their due with her social history of the Broad Band, the women who made the internet what it is today. Learn from Ada Lovelace, the daughter of Lord Byron, who wove numbers into the first program for a mechanical computer in 1842. Seek inspiration from Grace Hopper, the tenacious mathematician who democratized computing by leading the charge for machine-independent programming languages after World War II. Meet Elizabeth "Jake" Feinler, the one-woman Google who kept the earliest version of the Internet online, and Stacy Horn, who ran one of the first-ever social networks on a shoestring out of her New York City apartment in the 1980s. Evans shows us how these women built and colored the technologies we can't imagine life without.Join the ranks of the pioneers who defied social convention and the longest odds to become database poets, information-wranglers, hypertext dreamers, and glass ceiling-shattering dot com-era entrepreneurs.

    It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    Distinguishing agents (e.g., molecules, cells, animals, and species) from their interactions (e.g., chemical reactions, immune system responses, sexual reproduction, and evolution), Flake argues that it is the computational properties of interactions that account for much of what we think of as beautiful and interesting. From this basic thesis, Flake explores what he considers to be today's four most interesting computational topics: fractals, chaos, complex systems, and adaptation.Each of the book's parts can be read independently, enabling even the casual reader to understand and work with the basic equations and programs. Yet the parts are bound together by the theme of the computer as a laboratory and a metaphor for understanding the universe. The inspired reader will experiment further with the ideas presented to create fractal landscapes, chaotic systems, artificial life forms, genetic algorithms, and artificial neural networks.

    Vivid photos capture these historically important machinesincluding the Eniac, Crays 13, Apple I and IIwhile authoritative text profiles each, telling the stories of their innovations and peculiarities. Thirty-five machines are profiled in over 100 extraordinary color photographs, making Core Memory a surprising addition to the library of photography collectors and the ultimate geek-chic gift.

    Vaughn Vernon couples guided approaches to implementation with modern architectures, highlighting the importance and value of focusing on the business domain while balancing technical considerations.Building on Eric Evans’ seminal book, Domain-Driven Design, the author presents practical DDD techniques through examples from familiar domains. Each principle is backed up by realistic Java examples–all applicable to C# developers–and all content is tied together by a single case study: the delivery of a large-scale Scrum-based SaaS system for a multitenant environment.The author takes you far beyond “DDD-lite” approaches that embrace DDD solely as a technical toolset, and shows you how to fully leverage DDD’s “strategic design patterns” using Bounded Context, Context Maps, and the Ubiquitous Language. Using these techniques and examples, you can reduce time to market and improve quality, as you build software that is more flexible, more scalable, and more tightly aligned to business goals.

    It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    Simply stated, it asks whether every problem whose solution can be quickly checked by computer can also be quickly solved by computer. The Golden Ticket provides a nontechnical introduction to P-NP, its rich history, and its algorithmic implications for everything we do with computers and beyond. Lance Fortnow traces the history and development of P-NP, giving examples from a variety of disciplines, including economics, physics, and biology. He explores problems that capture the full difficulty of the P-NP dilemma, from discovering the shortest route through all the rides at Disney World to finding large groups of friends on Facebook. The Golden Ticket explores what we truly can and cannot achieve computationally, describing the benefits and unexpected challenges of this compelling problem.

    With step-by-step instructions, complete scripts, and expert tips to guide readers, this work gets right down to business - after grounding readers with separate discussions of first the scripting language (PHP) and then the database program (MySQL), it goes on to cover security, sessions and cookies, and using additional Web tools.