What many users don't realize is that the deceptively simple components that make Google so easy to use are the same features that generously unlock security flaws for the malicious hacker. Vulnerabilities in website security can be discovered through Google hacking, techniques applied to the search engine by computer criminals, identity thieves, and even terrorists to uncover secure information. This book beats Google hackers to the punch, equipping web administrators with penetration testing applications to ensure their site is invulnerable to a hacker's search. Penetration Testing with Google Hacks explores the explosive growth of a technique known as "Google Hacking." When the modern security landscape includes such heady topics as "blind SQL injection" and "integer overflows," it's refreshing to see such a deceptively simple tool bent to achieve such amazing results; this is hacking in the purest sense of the word. Readers will learn how to torque Google to detect SQL injection points and login portals, execute port scans and CGI scans, fingerprint web servers, locate incredible information caches such as firewall and IDS logs, password databases, SQL dumps and much more - all without sending a single packet to the target Borrowing the techniques pioneered by malicious "Google hackers," this talk aims to show security practitioners how to properly protect clients from this often overlooked and dangerous form of informationleakage. *First book about Google targeting IT professionals and security leaks through web browsing. *Author Johnny Long, the authority on Google hacking, will be speaking about "Google Hacking" at the Black Hat 2004 Briefing. His presentation on penetrating security flaws with Google is expected to create a lot of buzz and exposure for the topic. *Johnny Long's Web site hosts the largest repository of Google security exposures and is the most popular destination for security professionals who want to learn about the dark side of Google.

    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.

    Max explains to you why programmers suck, and how to suck less as a programmer. There's just too much complex stuff in the world. Complex stuff can't be used, and it breaks too easily. Complexity is stupid. Simplicity is smart.Understanding Software covers many areas of programming, from how to write simple code to profound insights into programming, and then how to suck less at what you do! You'll discover the problems with software complexity, the root of its causes, and how to use simplicity to create great software. You'll examine debugging like you've never done before, and how to get a handle on being happy while working in teams.Max brings a selection of carefully crafted essays, thoughts, and advice about working and succeeding in the software industry, from his legendary blog Code Simplicity. Max has crafted forty-three essays which have the power to help you avoid complexity and embrace simplicity, so you can be a happier and more successful developer.Max's technical knowledge, insight, and kindness, has earned him code guru status, and his ideas will inspire you and help refresh your approach to the challenges of being a developer. What you will learn See how to bring simplicity and success to your programming world Clues to complexity - and how to build excellent software Simplicity and software design Principles for programmers The secrets of rockstar programmers Max's views and interpretation of the Software industry Why Programmers suck and how to suck less as a programmer Software design in two sentences What is a bug? Go deep into debugging About the Author Max Kanat-Alexander is the Technical Lead for Code Health at Google, where he does various work that helps other software engineers be more productive, including writing developer tools, creating educational programs, guiding refactoring efforts, and more.His roles at Google have included Tech Lead for YouTube on the Xbox, work on the Java JDK, JVM, and other aspects of Java for Google, and Technical Lead for Engineering Practices for YouTube, where he's supported developers across all of YouTube in best practices and engineering productivity. Max is a former Chief Architect of the Bugzilla Project, where he was one of the two main developers of the well-known Bugzilla Bug-Tracking System, used by thousands of organizations worldwide. Max also writes the legendary programming industry blog, Code Simplicity, where he challenges Complexity and embraces Simplicity for the programming industry.Max has been involved for several years at Google with enabling developers to work more effectively and helping shape engineering practice, and in this highly readable collection of essays you can share the best of his experience. Table of Contents Part One: Principles for Programmers Part Two: Software Complexity and its Causes Part Three: Simplicity and Software Design Part Four: Debugging Part Five:

    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.

    Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is enhanced by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.

    The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors

    

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    It provides all of JavaScript's functionality wrapped in a cleaner, more succinct syntax. In the first book on this exciting new language, CoffeeScript guru Trevor Burnham shows you how to hold onto all the power and flexibility of JavaScript while writing clearer, cleaner, and safer code.CoffeeScript: Accelerated JavaScript Development offers a thorough introduction to this new language, starting from the basics. You'll learn to use time-saving features like list comprehensions and splats, organize your code into modules with extensible classes, and deploy your work to multiple environments. Each chapter is example-driven and includes challenging exercises to push your CoffeeScript know-how further. Through the course of the book, you'll build a fast-paced multiplayer word game-writing both the client (with jQuery) and server (with Node.js) in CoffeeScript. And because the two languages are so deeply intertwined, you'll deepen your understanding of JavaScript along the way. CoffeeScript makes it easier than ever to write powerful, standards-compliant JavaScript code. CoffeeScript: Accelerated JavaScript Development lets you start doing it today.

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

    It includes a complete chapter on C++ and an overall organization designed to appeal to the many programmers who view C as a stepping stone to C++ and the object-oriented paradigm. This edition also features an increased emphasis on modules and ADTs, which are essential concepts for creating reusable code and which show how to use header files to tie together a multi-file program. computer science students.

    100% complete coverage of all objectives for exam RH302 Exam Readiness Checklist at the front of the book--you're ready for the exam when all objectives on the list are checked off Inside the Exam sections in every chapter highlight key exam topics covered Real-world exercises modeled after hands-on exam scenarios Two complete lab-based exams simulate the format, tone, topics, and difficulty of the real exam Bonus content (available for download) includes installation screen review, basic instructions for using VMware and Xen as testbeds, and paper and pencil versions of the lab exams Covers all RH302 exam topics, including: Hardware installation and configuration The boot process Linux filesystem administration Package management and Kickstart User and group administration System administration tools Kernel services and configuration Apache and Squid Network file sharing services (NFS, FTP, and Samba) Domain Name System (DNS) E-mail (servers and clients) Extended Internet Services Daemon (xinetd), the Secure package, and DHCP The X Window System Firewalls, SELinux, and troubleshooting

    Why wade through a 600-page book when you can begin working productively in a matter of minutes? It's an ideal primer for Mac and PC users of the Internet who need to know a little bit about UNIX on the systems they visit.This book is the most effective introduction to UNIX in print. The fourth edition covers the highlights of the Linux operating system. It's a handy book for someone just starting with UNIX or Linux, as well as someone who encounters a UNIX system on the Internet. And it now includes a quick-reference card.Topics covered include: Linux operating system highlightsLogging in and logging outWindow systems (especially X/Motif)Managing UNIX files and directoriesSending and receiving mailRedirecting input/outputPipes and filtersBackground processingBasic network commandsv

    of Wisconsin-Madison) and Wichern (Texas A&M U.) present the newest edition of this college text on the statistical methods for describing and analyzing multivariate data, designed for students who have taken two or more statistics courses. The fifth edition includes the addition of seve