Old-fashioned entrepreneurship combined with scientific know-how inspired now famous computer engineers to create the technology that became IBM. Wartime needs drove the giant ENIAC, the first fully electronic computer. Later, the PC enabled modes of computing that liberated people from room-sized, mainframe computers. This second edition now extends beyond the development of Microsoft Windows and the Internet, to include open source operating systems like Linux, and the rise again and fall and potential rise of the dot.com industries.

    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.

    According to Neil Gershenfeld, the renowned MIT scientist and inventor, the next big thing is personal fabrication–the ability to design and produce your own products, in your own home, with a machine that combines consumer electronics with industrial tools. Personal fabricators (PF’s) are about to revolutionize the world just as personal computers did a generation ago. PF’s will bring the programmability of the digital world to the rest of the world, by being able to make almost anything-including new personal fabricators. In FAB, Gershenfeld describes how personal fabrication is possible today, and how it is meeting local needs with locally developed solutions. He and his colleagues have created “fab labs” around the world, which, in his words, can be interpreted to mean “a lab for fabrication, or simply a fabulous laboratory.” Using the machines in one of these labs, children in inner-city Boston have made saleable jewelry from scrap material. Villagers in India used their lab to develop devices for monitoring food safety and agricultural engine efficiency. Herders in the Lyngen Alps of northern Norway are developing wireless networks and animal tags so that their data can be as nomadic as their animals. And students at MIT have made everything from a defensive dress that protects its wearer’s personal space to an alarm clock that must be wrestled into silence. These experiments are the vanguard of a new science and a new era-an era of “post-digital literacy” in which we will be as familiar with digital fabrication as we are with the of information processing. In this groundbreaking book, the scientist pioneering the revolution in personal fabrication reveals exactly what is being done, and how. The technology of FAB will allow people to create the objects they desire, and the kind of world they want to live in.

    In this richly illustrated book, accessible examples are used to show how information theory can be understood in terms of everyday games like '20 Questions', and the simple MatLab programs provided give hands-on experience of information theory in action. Written in a tutorial style, with a comprehensive glossary, this text represents an ideal primer for novices who wish to become familiar with the basic principles of information theory.Download chapter 1 from http://jim-stone.staff.shef.ac.uk/Boo...

    Renowned for her lucid, accessible prose, Epp explains complex, abstract concepts with clarity and precision. This book presents not only the major themes of discrete mathematics, but also the reasoning that underlies mathematical thought. Students develop the ability to think abstractly as they study the ideas of logic and proof. While learning about such concepts as logic circuits and computer addition, algorithm analysis, recursive thinking, computability, automata, cryptography, and combinatorics, students discover that the ideas of discrete mathematics underlie and are essential to the science and technology of the computer age. Overall, Epp's emphasis on reasoning provides students with a strong foundation for computer science and upper-level mathematics courses.

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

    As well as lucid descriptions of all the topics and many worked examples, it contains over 800 exercises. New stand-alone chapters give a systematic account of the 'special functions' of physical science, cover an extended range of practical applications of complex variables, and give an introduction to quantum operators. Further tabulations, of relevance in statistics and numerical integration, have been added. In this edition, half of the exercises are provided with hints and answers and, in a separate manual available to both students and their teachers, complete worked solutions. The remaining exercises have no hints, answers or worked solutions and can be used for unaided homework; full solutions are available to instructors on a password-protected web site, www.cambridge.org/9780521679718.

    In this one-of-a-kind account, you'll see how the developers responsible for these flaws patched the bugs—or failed to respond at all. As you follow Klein on his journey, you'll gain deep technical knowledge and insight into how hackers approach difficult problems and experience the true joys (and frustrations) of bug hunting.Along the way you'll learn how to:Use field-tested techniques to find bugs, like identifying and tracing user input data and reverse engineering Exploit vulnerabilities like NULL pointer dereferences, buffer overflows, and type conversion flaws Develop proof of concept code that verifies the security flaw Report bugs to vendors or third party brokersA Bug Hunter's Diary is packed with real-world examples of vulnerable code and the custom programs used to find and test bugs. Whether you're hunting bugs for fun, for profit, or to make the world a safer place, you'll learn valuable new skills by looking over the shoulder of a professional bug hunter in action.