With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    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.

    Legendary testing expert James Whittaker, until recently a Google testing leader, and two top Google experts reveal exactly how Google tests software, offering brand-new best practices you can use even if you're not quite Google's size...yet! Breakthrough Techniques You Can Actually Use Discover 100% practical, amazingly scalable techniques for analyzing risk and planning tests...thinking like real users...implementing exploratory, black box, white box, and acceptance testing...getting usable feedback...tracking issues...choosing and creating tools...testing "Docs & Mocks," interfaces, classes, modules, libraries, binaries, services, and infrastructure...reviewing code and refactoring...using test hooks, presubmit scripts, queues, continuous builds, and more. With these techniques, you can transform testing from a bottleneck into an accelerator-and make your whole organization more productive!

    This classic guide—fully updated for Windows Server 2003, Windows XP, and Windows 2000, including 64-bit extensions—describes the architecture and internals of the Windows operating system. You’ll find hands-on experiments you can use to experience Windows internal behavior firsthand, along with advanced troubleshooting information to help you keep your systems running smoothly and efficiently. Whether you’re a developer or a system administrator, you’ll find critical architectural insights that you can quickly apply for better design, debugging, performance, and support.Get in-depth, inside knowledge of the Windows operating system: Understand the key mechanisms that configure and control Windows, including dispatching, startup and shutdown, and the registry Explore the Windows security model, including access, privileges, and auditing Investigate internal system architecture using the kernel debugger and other tools Examine the data structures and algorithms that deal with processes, threads, and jobs Observe how Windows manages virtual and physical memory Understand the operation and format of NTFS, and troubleshoot file system access problems View the Windows networking stack from top to bottom, including mapping, APIs, name resolution, and protocol drivers Troubleshoot boot problems and perform crash analysis

     Master each chapter with free interactive exercises online. Live simulation lets you see your practice code run in your browser. 2,000 lines of color-keyed sample code break it all down into easy-to-learn chunks. Extra help through the rough spots so you're less likely to get stuck. Tested on non-coders—including the author's technophobe wife. Become fluent in all the JavaScript fundamentals, in half the time. Display alert messages to the user Gather information through prompts Manipulate variables Build statements Do math Use operators Concatenate text Run routines based on conditions Compare values Work with arrays Run automated routines Display custom elements on the webpage Generate random numbers Manipulate decimals Round numbers Create loops Use functions Find the current date and time Measure time intervals Create a timer Respond to the user's actions Swap images Control colors on the webpage Change any element on the webpage Improvise new HTML markup on the fly Use the webpage DOM structure Insert comments Situate scripts effectively Create and change objects Automate object creation Control the browser's actions Fill the browser window with custom content Check forms for invalid entries Deal with errors Make a more compelling website Increase user-friendliness Keep your user engaged

    Drawing on Lopp's management experiences at Apple, Netscape, Symantec, and Borland, this book is full of stories based on companies in the Silicon Valley where people have been known to yell at each other. It is a place full of dysfunctional bright people who are in an incredible hurry to find the next big thing so they can strike it rich and then do it all over again. Among these people are managers, a strange breed of people who through a mystical organizational ritual have been given power over your future and your bank account.Whether you're an aspiring manager, a current manager, or just wondering what the heck a manager does all day, there is a story in this book that will speak to you.

    This cookbook includes more than 100 recipes to help you take advantage of REST, HTTP, and the infrastructure of the Web. You'll learn ways to design RESTful web services for client and server applications that meet performance, scalability, reliability, and security goals, no matter what programming language and development framework you use.Each recipe includes one or two problem statements, with easy-to-follow, step-by-step instructions for solving them, as well as examples using HTTP requests and responses, and XML, JSON, and Atom snippets. You'll also get implementation guidelines, and a discussion of the pros, cons, and trade-offs that come with each solution.Learn how to design resources to meet various application scenariosSuccessfully design representations and URIsImplement the hypertext constraint using links and link headersUnderstand when and how to use Atom and AtomPubKnow what and what not to do to support cachingLearn how to implement concurrency controlDeal with advanced use cases involving copying, merging, transactions, batch processing, and partial updatesSecure web services and support OAuth