Understanding the design, implementation, and workings of Mac OS X requires examination of several technologies that differ in their age, origins, philosophies, and roles. Mac OS X Internals: A Systems Approach is the first book that dissects the internals of the system, presenting a detailed picture that grows incrementally as you read. For example, you will learn the roles of the firmware, the bootloader, the Mach and BSD kernel components (including the process, virtual memory, IPC, and file system layers), the object-oriented I/O Kit driver framework, user libraries, and other core pieces of software. You will learn how these pieces connect and work internally, where they originated, and how they evolved. The book also covers several key areas of the Intel-based Macintosh computers.A solid understanding of system internals is immensely useful in design, development, and debugging for programmers of various skill levels. System programmers can use the book as a reference and to construct a better picture of how the core system works. Application programmers can gain a deeper understanding of how their applications interact with the system. System administrators and power users can use the book to harness the power of the rich environment offered by Mac OS X. Finally, members of the Windows, Linux, BSD, and other Unix communities will find the book valuable in comparing and contrasting Mac OS X with their respective systems. Mac OS X Internals focuses on the technical aspects of OS X and is so full of extremely useful information and programming examples that it will definitely become a mandatory tool for every Mac OS X programmer.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    It is offered for sale in print format as a convenience.Get a head start evaluating Windows Azure - with technical insights from a Microsoft MVP Mitch Tulloch. This guide introduces the latest features and capabilities, with scenario-based advice on how the platform can meet the needs of your business. Get the high-level overview you need to begin preparing your deployment now.Topics include: Understanding Windows Azure Windows Azure Compute Services Windows Azure Network Services Windows Azure Data Services Windows Azure App Services Getting Started with Windows Azure

    Fundamentals of Data Structures in C++ offers a complete rendering of basic data structure implementations, enhanced by superior pedagogy and astute analyses.

    There are records of these kinds of people in ancient times, and we all know they are still alive and well today. But what we don’t know is what goes on inside their heads. Why would anyone kill for the sake of it? Why would someone that seemed so nice and so normal do such a terrible thing? What causes this kind of behavior? These and many more questions have flooded the minds of those that study criminal psychology for decades. If there was a way to know why they do what they do, it would be so much easier to counteract it. If there was a way we could prevent this from ever happening in the first place, we would all be a lot better off than we are now, trying to figure out what is causing this behavior. But now, with this book, you can get a glimpse inside the mind of a serial killer, and see why they are the way they are. There is a lot that doesn’t meet the eye, and these things could potentially change the way we deal with violent offenders forever. We could potentially treat the symptoms from the beginning and prevent another serial killer from ever entering the world. This book covers it all, from what is really going on and what caused it to how we can prevent it. This book is going to change the way you view violent offenders, and show you we really can make a difference. Read on to discover how you can be a part of the solution to this problem, and how we can end this kind of behavior forever. Just scroll up and click the "Buy now with 1-Click" button to get the book now! $2.99 Only Today! Keywords: criminal, psychology, mind, profiling, understanding, sociology, guide, annotated, legendary, victimology

    * A beautifully designed resource chronicling one of gaming's most massive, dynamic universes! * MMORPG.com's Game of the Year 2009–2011! * 2014 marks the entry of EVE Online into its second decade!

    Each word in Biblical Hebrew and Biblical Aramaic is numbered, presented in Hebrew script and in transliteration and is accompanied by a pronunciation guide. Each word is defined, and the translation(s) of that word in the Authorized English Version are presented. Strong's work was originally published in 1890 under the title A Concise Dictionary of the Words in the Hebrew Bible; with their Renderings in the Authorized English Version. It was bound together with Strong's Exhaustive Concordance of the Bible.

    This text helps develop in readers the skills, knowledge and strategies needed to read and interpret research reports and to evaluate the quality of such reports.

    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

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    Over 450 photographs, drawings, and diagrams reveal in exquisite detail the hows, whys, and how-to's of the traditional craft of guitarmaking, all accompanied by fascinating historical and technical notes. A comprehensive bibliography; a list of tools, materials, and supply sources; and a full index complete this uniquely authoritative reference -- and essential acquisition -- for guitar and craft enthusiasts, woodworkers, and students of instrument making everywhere.

    She believes you can too.

    

    It rejoices in men and women made of the Wrong Stuff: writers who believed in the power of words, but could never quite find the rights ones; artists and performers who indulged their creative impulse with a passion, if not a sense of the ridiculous, an eye for perspective or the ability to hold down a tune; scientists and businessmen who never quite managed to quit while they were ahead; and sportsmen who seemed to manage always to snatch defeat from the jaws of victory. Like Walter Oudney, one of three men chosen to find the source of the River Niger in Africa, who could not ride a horse, nor speak any foreign languages and who had never travelled more than 30 miles beyond his native Edinburgh; or the explorer-priest Michel Alexandre de Baize, who set off to explore the African continent from east to west equipped with 24 umbrellas, some fireworks, two suits of armor, and a portable organ; or the Scottish army which decided to invade England in 1349 - during the Black Death. Entries include: briefest career in dentistry; least successful bonding exercise; most futile attempt to find a lost tribe; most pointless lines of research by someone who should have known better; least successful celebrity endorsement; least convincing excuse for a war; worst poetic tribute to a root vegetable; least successful display of impartiality by a juror; Devon Loch - sporting metaphor for blowing un unblowable lead; least dignified exit from office by a French president; and least successful expedition by camel.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.