This book brings you up-to-date with the latest changes in this crucial service.The fifth edition covers BIND 9.3.2, the most recent release of the BIND 9 series, as well as BIND 8.4.7. BIND 9.3.2 contains further improvements in security and IPv6 support, and important new features such as internationalized domain names, ENUM (electronic numbering), and SPF (the Sender Policy Framework).Whether you're an administrator involved with DNS on a daily basis or a user who wants to be more informed about the Internet and how it works, you'll find that this book is essential reading.Topics include:What DNS does, how it works, and when you need to use it How to find your own place in the Internet's namespace Setting up name servers Using MX records to route mail Configuring hosts to use DNS name servers Subdividing domains (parenting) Securing your name server: restricting who can query your server, preventing unauthorized zone transfers, avoiding bogus servers, etc. The DNS Security Extensions (DNSSEC) and Transaction Signatures (TSIG) Mapping one name to several servers for load sharing Dynamic updates, asynchronous notification of change to a zone, and incremental zone transfers Troubleshooting: using nslookup and dig, reading debugging output, common problems DNS programming using the resolver library and Perl's Net::DNS module

    With this hands-on reference, you'll focus on implementation rather than theory, and discover why the RESTful method is far better than technologies like CORBA and SOAP. It's easy to get started with services based on the REST architecture. RESTful Java with JAX-RS includes a technical guide that explains REST and JAX-RS, how they work, and when to use them. With the RESTEasy workbook that follows, you get step-by-step instructions for installing, configuring, and running several working JAX-RS examples using the JBoss RESTEasy implementation of JAX-RS.Work on the design of a distributed RESTful interface, and develop it in Java as a JAX-RS serviceDispatch HTTP requests in JAX-RS, and learn how to extract information from themDeploy your web services within Java Enterprise Edition using the Application class, Default Component Model, EJB Integration, Spring Integration, and JPADiscover several options for securing your web servicesLearn how to implement RESTful design patterns using JAX-RSWrite RESTful clients in Java using libraries and frameworks such as java.net.URL, Apache HTTP Client, and RESTEasy Proxy

    The second edition of this book helps you prepare for the PMP certification exam using a visually rich format designed for the way your brain works. You'll find a full-length sample exam included inside the book. More than just proof of passing a test, a PMP certification means that you have the knowledge to solve most common project problems. But studying for a difficult four-hour exam on project management isn't easy, even for experienced project managers. Drawing on the latest research in neurobiology, cognitive science, and learning theory, Head First PMP offers you a multi-sensory experience that helps the material stick, not a text-heavy approach that puts you to sleep. This book will help you:Learn PMP's underlying concepts to help you understand the PMBOK principles and pass the certification exam with flying colorsGet 100% coverage of the latest principles and certification objectives in The PMBOK Guide, Fourth Edition, including two new processes: Collect Requirements and Identify StakeholdersMake use of a thorough and effective preparation guide with hundreds of practice questions and exam strategiesExplore the material through puzzles, games, problems, and exercises that make learning easy and entertainingHead First PMP puts project management principles into context to help you understand, remember, and apply them -- not just on the exam, but also on the job.

    

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    You'll also receive updates when significant changes are made, as well as the final ebook version. Embedded Android is for Developers wanting to create embedded systems based on Android and for those wanting to port Android to new hardware, or creating a custom development environment. Hackers and moders will also find this an indispensible guide to how Android works.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    Intermediate to advanced system administrators will find more than 100 tried-and-tested scripts they can copy and use immediately.Updated for PowerShell 3.0, this comprehensive cookbook includes hands-on recipes for common tasks and administrative jobs that you can apply whether you’re on the client or server version of Windows. You also get quick references to technologies used in conjunction with PowerShell, including format specifiers and frequently referenced registry keys to selected .NET, COM, and WMI classes.Learn how to use PowerShell on Windows 8 and Windows Server 2012Tour PowerShell’s core features, including the command model, object-based pipeline, and ubiquitous scriptingMaster fundamentals such as the interactive shell, pipeline, and object conceptsPerform common tasks that involve working with files, Internet-connected scripts, user interaction, and moreSolve tasks in systems and enterprise management, such as working with Active Directory and the filesystem

    Team leads usually have little to no idea how to handle people related issues – issues that affect how the morale, quality of work, and overall performance of the team, and of course impacts how easy or hard it is to implement “the new stuff”.Most team leaders are clueless as to how to handle their manager giving them an impossible due date, a team member reluctant to try anything new, or another team member teaching all the other members practices from 25 years ago that today only hurt the team.Why?No one teaches that to software team leads. Team leads today, in the overwhelming majority of places, are just developers who worked hard and stayed with the company long enough to be promoted. But they have no people or management skills - and those are very painfully needed when you are trying to drive the things you believe in inside an organization that has very little interest in changing.Team leadership is the next big thing that software developers need to conquer, or none of this unit testing, TDD, Agile or Lean thing is going to catch on, except in very small circles, that, by chance, happen to have the right people leading their teams.

    But while Metasploit is used by security professionals everywhere, the tool can be hard to grasp for first-time users. Metasploit: The Penetration Tester's Guide fills this gap by teaching you how to harness the Framework and interact with the vibrant community of Metasploit contributors.Once you've built your foundation for penetration testing, you'll learn the Framework's conventions, interfaces, and module system as you launch simulated attacks. You'll move on to advanced penetration testing techniques, including network reconnaissance and enumeration, client-side attacks, wireless attacks, and targeted social-engineering attacks.Learn how to:Find and exploit unmaintained, misconfigured, and unpatched systems Perform reconnaissance and find valuable information about your target Bypass anti-virus technologies and circumvent security controls Integrate Nmap, NeXpose, and Nessus with Metasploit to automate discovery Use the Meterpreter shell to launch further attacks from inside the network Harness standalone Metasploit utilities, third-party tools, and plug-ins Learn how to write your own Meterpreter post exploitation modules and scripts You'll even touch on exploit discovery for zero-day research, write a fuzzer, port existing exploits into the Framework, and learn how to cover your tracks. Whether your goal is to secure your own networks or to put someone else's to the test, Metasploit: The Penetration Tester's Guide will take you there and beyond.

    This indispensible and full-color book provides practical guidance on this growing field and shares valuable UX advice that you can put into practice immediately on your own projects. The authors examine why UX is gaining so much interest from web designers, graduates, and career changers and looks at the new UX tools and ideas that can help you do your job better. In addition, you'll benefit from the unique insight the authors provide from their experiences of working with some of the world's best-known companies, learning how to take ideas from business requirements, user research, and documentation to create and develop your UX vision.Explains how to create documentation that clearly communicates the vision for the UX design and the blueprint for how it's going to be developed Provides practical guidance that you can put to work right away on their own projects Looks at the new UX tools and ideas that are born every day, aimed at helping you do your job better and more efficiently Covers a variety of topics including user journeys, task models, funnel diagrams, content audits, sitemaps, wireframes, interactive prototypes, and more Communicating the User Experience is an ideal resource for getting started with creating UX documentation.

    

    This complete guide shows you how to automate your build, integration, release, and deployment processes with Jenkins—and demonstrates how CI can save you time, money, and many headaches. Ideal for developers, software architects, and project managers, Jenkins: The Definitive Guide is both a CI tutorial and a comprehensive Jenkins reference. Through its wealth of best practices and real-world tips, you'll discover how easy it is to set up a CI service with Jenkins. Learn how to install, configure, and secure your Jenkins server Organize and monitor general-purpose build jobs Integrate automated tests to verify builds, and set up code quality reporting Establish effective team notification strategies and techniques Configure build pipelines, parameterized jobs, matrix builds, and other advanced jobs Manage a farm of Jenkins servers to run distributed builds Implement automated deployment and continuous delivery

    But how do you interpret those packets once you've captured them? And how can those packets help you to better understand what's going on under the hood of your network? Practical Packet Analysis shows how to use Wireshark to capture and then analyze packets as you take an indepth look at real-world packet analysis and network troubleshooting. The way the pros do it.Wireshark (derived from the Ethereal project), has become the world's most popular network sniffing application. But while Wireshark comes with documentation, there's not a whole lot of information to show you how to use it in real-world scenarios. Practical Packet Analysis shows you how to:Use packet analysis to tackle common network problems, such as loss of connectivity, slow networks, malware infections, and more Build customized capture and display filters Tap into live network communication Graph traffic patterns to visualize the data flowing across your network Use advanced Wireshark features to understand confusing packets Build statistics and reports to help you better explain technical network information to non-technical usersBecause net-centric computing requires a deep understanding of network communication at the packet level, Practical Packet Analysis is a must have for any network technician, administrator, or engineer troubleshooting network problems of any kind.

    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