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.

    Cryptography is vital to keeping information safe, in an era when the formula to do so becomes more and more challenging. Written by a team of world-renowned cryptography experts, this essential guide is the definitive introduction to all major areas of cryptography: message security, key negotiation, and key management. You'll learn how to think like a cryptographer. You'll discover techniques for building cryptography into products from the start and you'll examine the many technical changes in the field.After a basic overview of cryptography and what it means today, this indispensable resource covers such topics as block ciphers, block modes, hash functions, encryption modes, message authentication codes, implementation issues, negotiation protocols, and more. Helpful examples and hands-on exercises enhance your understanding of the multi-faceted field of cryptography.An author team of internationally recognized cryptography experts updates you on vital topics in the field of cryptography Shows you how to build cryptography into products from the start Examines updates and changes to cryptography Includes coverage on key servers, message security, authentication codes, new standards, block ciphers, message authentication codes, and more Cryptography Engineering gets you up to speed in the ever-evolving field of cryptography.

    Together, they ruled big business. They transformed popular culture. And they provoked a national controversy. More than anything, they lived a unique and rollicking American Dream, escaping the broken homes of their youth to produce the most notoriously successful game franchises in history—Doom and Quake— until the games they made tore them apart. This is a story of friendship and betrayal, commerce and artistry—a powerful and compassionate account of what it's like to be young, driven, and wildly creative.

    After introducing the basic concepts, the book examines techniques for modeling probability density functions and the properties and merits of the multi-layerperceptron and radial basis function network models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalization in neural networks, and Bayesian techniques and their applications. Designed as a text, with over 100exercises, this fully up-to-date work will benefit anyone involved in the fields of neural computation and pattern recognition.

    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.

    NOTE: this Alpha Edition is missing some chapters and may contain errors. See http://saasbook.info for details.

    Section I: Exploits 202; Chapter 1: Survival; Chapter 2: Basic Exploits; Chapter 3: Advance Exploits; Chapter 4: Writing Shell Code; Section II: Vulnerability Analysis; Chapter 5: Passive Analysis; Chapter 6: Active Analysis; Chapter 7: Bug to Exploit; Chapter 8: Mitigation; Section III: Advanced System Hacks; Chapter 9: Advanced.

    In How the Internet Happened, he chronicles the whole fascinating story for the first time, beginning in a dusty Illinois basement in 1993, when a group of college kids set off a once-in-an-epoch revolution with what would become the first “dotcom.”Depicting the lives of now-famous innovators like Netscape’s Marc Andreessen and Facebook’s Mark Zuckerberg, McCullough also reveals surprising quirks and unknown tales as he tracks both the technology and the culture around the internet’s rise. Cinematic in detail and unprecedented in scope, the result both enlightens and informs as it draws back the curtain on the new rhythm of disruption and innovation the internet fostered, and helps to redefine an era that changed every part of our lives.

     Limited Time Offer: Buy CompTIA(R) A+ 220-801 and 220-802 Exam Cram and receive a 10% off discount code for the CompTIA A+ 220-801 and 220-802 exams. To receive your 10% off discount code:Register your product at pearsonITcertification.com/registerFollow the instructionsGo to your Account page and click on "Access Bonus Content" CompTIA(R) A+ 220-801 and 220-802 Exam Cram, Sixth Edition is the perfect study guide to help you pass CompTIA's A+ 220-801 and 220-802 exams. It provides coverage and practice questions for every exam topic, including substantial new coverage of Windows 7, new PC hardware, tablets, smartphones, and professional-level networking and security. The book presents you with an organized test preparation routine through the use of proven series elements and techniques. Exam topic lists make referencing easy. Exam Alerts, Sidebars, and Notes interspersed throughout the text keep you focused on what you need to know. Cram Quizzes help you assess your knowledge, and the Cram Sheet tear card is the perfect last minute review. Covers the critical information you'll need to know to score higher on your CompTIA A+ 220-801 and 220-802 exams!Deploy and administer desktops and notebooks running Windows 7, Vista, or XPUnderstand, install, and troubleshoot motherboards, processors, and memoryTest and troubleshoot power-related problemsUse all forms of storage, including new Blu-ray and Solid State (SSD) devicesWork effectively with mobile devices, including tablets and smartphonesInstall, configure, and troubleshoot both visible and internal laptop componentsConfigure Windows components and applications, use Windows administrative tools, and optimize Windows systemsRepair damaged Windows environments and boot errorsWork with audio and video subsystems, I/O devices, and the newest peripheralsInstall and manage both local and network printersConfigure IPv4 and understand TCP/IP protocols and IPv6 changesInstall and configure SOHO wired/wireless networks and troubleshoot connectivityImplement secure authentication, prevent malware attacks, and protect data Companion CDThe companion CD contains a digital edition of the Cram Sheet and the powerful Pearson IT Certification Practice Test engine, complete with hundreds of exam-realistic questions and two complete practice exams. The assessment engine offers you a wealth of customization options and reporting features, laying out a complete assessment of your knowledge to help you focus your study where it is needed most. Pearson IT Certifcation Practice Test Minimum System RequirementsWindows XP (SP3), WIndows Vista (SP2), or Windows 7Microsoft .NET Framework 4.0 ClientPentium-class 1 GHz processor (or equivalent)512 MB RAM650 MB disk space plus 50 MB for each downloaded practice exam David L. Prowse is an author, computer network specialist, and technical trainer. Over the past several years he has authored several titles for Pearson Education, including the well-received CompTIA A+ Exam Cram and CompTIA Security+ Cert Guide. As a consultant, he installs and secures the latest in computer and networking technology. He runs the website www.davidlprowse.com, where he gladly answers questions from students and readers.

    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.

    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.

    This book covers a range of genres, including action, adventure, and puzzle games complete with professional quality sound effects and visuals. It discusses game design theory and features practical examples of how this can be applied to making games that are more fun to play. Game Maker allows games to be created using a simple drag-and-drop interface, so you don't need to have any prior coding experience. It includes an optional programming language for adding advanced features to your games, when you feel ready to do so. You can obtain more information by visiting book.gamemaker.nl. The authors include the creator of the Game Maker tool and a former professional game programmer, so you'll glean understanding from their expertise. The book also includes a DVD containing Game Maker software and all of the game projects that are created in the book—plus a host of professional-quality graphics and sound effects that you can use in your own games.

    Missile trajectories. Cornering dynamics in speeding cars. By applying the laws of physics, you can realistically model nearly everything in games that bounces around, flies, rolls, slides, or isn't sitting still, to create compelling, believable content for computer games, simulations, and animation. "Physics for Game Developers" serves as the starting point for those who want to enrich games with physics-based realism.Part one is a mechanics primer that reviews basic concepts and addresses aspects of rigid body dynamics, including kinematics, force, and kinetics. Part two applies these concepts to specific real-world problems, such as projectiles, boats, airplanes, and cars. Part three introduces real-time simulations and shows how they apply to computer games. Many specific game elements stand to benefit from the use of real physics, including: The trajectory of rockets and missiles, including the effects of fuel burn offThe collision of objects such as billiard ballsThe stability of cars racing around tight curvesThe dynamics of boats and other waterborne vehiclesThe flight path of a baseball after being struck by a batThe flight characteristics of airplanesYou don't need to be a physics expert to learn from "Physics for Game Developers, " but the author does assume you know basic college-level classical physics. You should also be proficient in trigonometry, vector and matrix math (reference formulas and identities are included in the appendixes), and college-level calculus, including integration and differentiation of explicit functions. Although the thrust of the book involves physics principles and algorithms, it should be noted that the examples are written in standard C and use Windows API functions.

    This work represents the views of a mathematician on the analogies between computing machines and the living human brain.

    Stay in the know, spot trends as they happen, and push your business to new limits. This e-book introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples.