Turing Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be "computable," creating the field of computability theory in the process, a foundation of present-day computer programming.The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks, and others.Interwoven into the narrative are the highlights of Turing's own life: his years at Cambridge and Princeton, his secret work in cryptanalysis during World War II, his involvement in seminal computer projects, his speculations about artificial intelligence, his arrest and prosecution for the crime of "gross indecency," and his early death by apparent suicide at the age of 41.

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    A new four-part organizational structure increases the flexibility of the text, and all material is presented in a straightforward manner accompanied by an array of examples and visual diagrams.

    By following the recommendations of the Association of Computing Machinery's Java Task Force, this first edition text adopts a modern objects-first approach that introduces readers to useful hierarchies from the very beginning.KEY TOPICS: Introduction; Programming by Example; Expressions; Statement Forms; Methods; Objects and Classes; Objects and Memory; Strings and Characters; Object-Oriented Graphics; Event-Driven Programs; Arrays and ArrayLists; Searching and Sorting; Collection Classes; Looking Ahead.MARKET: A modern objects-first approach to the Java programming language that introduces readers to useful class hierarchies from the very beginning.

    This operating system now serves as corporate hubs, Web servers, academic research platforms, and program development systems. All along it's also managed to keep its original role as an enjoyable environment for personal computing, learning system administration and programming skills, and all-around hacking.This book, now in its third edition, has been widely recognized for years in the Linux community as the getting-started book people need. It goes into depth about configuration issues that often trip up users but are glossed over by other books.A complete, UNIX-compatible operating system developed by volunteers on the Internet, Linux is distributed freely in electronic form and at a low cost from many vendors. Developed first on the PC, it has been ported to many other architectures and can now support such heavy-duty features as multiprocessing, RAID, and clustering.Software packages on Linux include the Samba file server and Apache Web server; the X Window System (X11R6); TCP/IP networking (including PPP, SSH, and NFS support); popular software tools such as Emacs and TeX; a complete software development environment including C, C++, Java, Perl, Tcl/Tk, and Python; libraries, debuggers, multimedia support, scientific and database applications, and much more. Commercial applications that run on Linux range from end-user tools like word processors and spreadsheets to mission-critical software like the Oracle, Sybase, Informix, and IBM DB/2 database management systems.Running Linux has all the information you need to understand, install, and start using the Linux operating system. This includes a comprehensive installation tutorial, complete information on system maintenance, tools for document development and programming, and guidelines for network, file, printer, and Web site administration.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    The text is divided into four parts: circuits, electronics, digital systems, and electromagnetics. Although it delves in depth into each of these topics, the text represents more than your basic survey of the basics of electrical engineering. A solid understanding of the fundamental principles on which modern electrical engineering is based is also provided. This edition includes a chapter on circuit analysis software SPICE, with a detailed discussion of the PC version known as PSPICE (from MicroSim Corp.). Numerous drill exercises have been added to this new edition, reinforcing ideas presented in the examples. There are over 1,000 end-of-chapter problems. This text is suitable for a variety of electrical engineering courses. It can be used as a text for an introduction to electrical engineering for both majors and non-majors or both, or can be split and the various chapters utilized for an introduction to circuits course, a first electronics course, or for a course on digital electronics and logic design.

    This book covers it all! Encrypting your private files, securing your PC, masking your online footsteps, and all while giving you peace of mind with TOTAL 100% ANONYMITY. Don't waste months scouring the internet for info. Just read this! You'll be hooked in five minutes. It's all here: CIA techniques, how the NSA catches Tor users, Truecrypt and the FBI, nuking tracking cookies, private browsing, preventing identity theft. I will show you: -How to Be Anonymous Online -Step by Step Guides for Tor, Freenet, I2P, VPNs, Usenet and more -Browser Fingerprinting -Anti-Hacking and Counter-Forensic Techniques -Photo & Video Metadata -How to Encrypt Files (I make this super simple) -How to Defeat NSA Spying -How to Browse the Deep Web -How to Protect Your Identity -How to Hide Anything! You've probably read How to Be Invisible by J. J. Luna and Incognito Toolkit by Rob Robideau, and while they are fine books, you need this companion piece to take it to the next level!

    But what will this future look like? In 2062, world-leading researcher Toby Walsh considers the impact AI will have on work, war, economics, politics, everyday life and even death. Will automation take away most jobs? Will robots become conscious and take over? Will we become immortal machines ourselves, uploading our brains to the cloud? How will politics adjust to the post-truth, post-privacy digitised world? When we have succeeded in building intelligent machines, how will life on this planet unfold?Based on a deep understanding of technology, 2062 describes the choices we need to make today to ensure that the future remains bright.‘Clarity and sanity in a world full of fog and uncertainty – a timely book about the race to remain human.’—RICHARD WATSON, author of Digital Vs. Human and futurist-in-residence at Imperial College, London‘One of the deepest questions facing humanity, pondered by a mind well and truly up to the task.’—ADAM SPENCER, broadcaster

    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

    

    With this concise book, you will learn how to use the latest version of this W3C standard to retrieve and manipulate the increasing amount of public and private data available via SPARQL endpoints. Several open source and commercial tools already support SPARQL, and this introduction gets you started right away.Begin with how to write and run simple SPARQL 1.1 queries, then dive into the language's powerful features and capabilities for manipulating the data you retrieve. Learn what you need to know to add to, update, and delete data in RDF datasets, and give web applications access to this data.Understand SPARQL’s connection with RDF, the semantic web, and related specificationsQuery and combine data from local and remote sourcesCopy, convert, and create new RDF dataLearn how datatype metadata, standardized functions, and extension functions contribute to your queriesIncorporate SPARQL queries into web-based applications

    There are also guides for further reading, and a new glossary of terms such as mentalese, connectionism, and the homunculus fallacy.

    Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

    Displaying extraordinary creativity and programming virtuosity, Alexandrescu offers a cutting-edge approach to design that unites design patterns, generic programming, and C++, enabling programmers to achieve expressive, flexible, and highly reusable code. This book introduces the concept of generic components--reusable design templates that produce boilerplate code for compiler consumption--all within C++. Generic components enable an easier and more seamless transition from design to application code, generate code that better expresses the original design intention, and support the reuse of design structures with minimal recoding. The author describes the specific C++ techniques and features that are used in building generic components and goes on to implement industrial strength generic components for real-world applications. Recurring issues that C++ developers face in their day-to-day activity are discussed in depth and implemented in a generic way. These include: Policy-based design for flexibility Partial template specialization Typelists--powerful type manipulation structures Patterns such as Visitor, Singleton, Command, and Factories Multi-method engines For each generic component, the book presents the fundamental problems and design options, and finally implements a generic solution.