It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    As a professional C++ developer and former Harvard teaching fellow, I know what you need to know to be a great C++ programmer, and I know how to teach it, one step at a time. I know where people struggle, and why, and how to make it clear. I cover every step of the programming process, including:Getting the tools you need to program and how to use them*Basic language feature like variables, loops and functions*How to go from an idea to code*A clear, understandable explanation of pointers*Strings, file IO, arrays, references*Classes and advanced class design*C++-specific programming patterns*Object oriented programming*Data structures and the standard template library (STL)Key concepts are reinforced with quizzes and over 75 practice problems.

    Each chapter addresses de-facto standards, popular technologies, and design principles applicable to a wide variety of systems. Complete with chapter summaries, end-of-chapter exercises and bibliographies, Distributed Operating Systems concludes with a set of case studies that provide real-world insights into four distributed operating systems.

    Sold in over 85 countries and translated into more than 5 languages.---------------Want to get started on data science?Our promise: no math added.This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.Popular concepts covered include:- A/B Testing- Anomaly Detection- Association Rules- Clustering- Decision Trees and Random Forests- Regression Analysis- Social Network Analysis- Neural NetworksFeatures:- Intuitive explanations and visuals- Real-world applications to illustrate each algorithm- Point summaries at the end of each chapter- Reference sheets comparing the pros and cons of algorithms- Glossary list of commonly-used termsWith this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

    Itzik Ben-Gan explains key T-SQL concepts and helps you apply your knowledge with hands-on exercises. The book first introduces T-SQL's roots and underlying logic. Next, it walks you through core topics such as single-table queries, joins, subqueries, table expressions, and set operators. Then the book covers more-advanced data-query topics such as window functions, pivoting, and grouping sets. The book also explains how to modify data, work with temporal tables, and handle transactions, and provides an overview of programmable objects. Microsoft Data Platform MVP Itzik Ben-Gan shows you how to: Review core SQL concepts and its mathematical roots Create tables and enforce data integrity Perform effective single-table queries by using the SELECT statement Query multiple tables by using joins, subqueries, table expressions, and set operators Use advanced query techniques such as window functions, pivoting, and grouping sets Insert, update, delete, and merge data Use transactions in a concurrent environment Get started with programmable objects-from variables and batches to user-defined functions, stored procedures, triggers, and dynamic SQL

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    That's the philosophy behind ethical hacking, and it's a growing field. Prepare for certification in this important area with this advanced study guide that covers all exam objectives for the challenging CEH Certified Ethical Hackers exam. The book provides full coverage of exam topics, real-world examples, and a CD with additional materials for extra review and practice. Covers ethics and legal issues, footprinting, scanning, enumeration, system hacking, trojans and backdoors, sniffers, denial of service, social engineering, session hijacking, hacking Web servers, Web application vulnerabilities, and more Walks you through exam topics and includes plenty of real-world scenarios to help reinforce concepts Includes a CD with review questions, bonus exams, and more study tools This is the ideal guide to prepare you for the new CEH certification exam. Reviews

    Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks.Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly.Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

    While learning these technologies, you will discover coding practices such as writing code that works on multiple browsers including mobile devices, how to use AJAX frameworks to add interactivity to your pages, and how to ensure your pages meet accessible requirements.Packed with real-world examples, the book not only teaches you how to write Web sites using XHTML, CSS and JavaScript, but it also teaches you design principles that help you create attractive web sites and practical advice on how to make web pages more usable. In addition, special checklists and appendices review key topics and provide helpful references that re-enforce the basics you've learned.Serves as an ideal beginners guide to writing web pages using XHTML Explains how to use CSS to make pages more appealing and add interactivity to pages using JavaScript and AJAX frameworks Share advice on design principles and how to make pages more attractive and offers practical help with usability and accessibility Features checklists and appendices that review key topics This introductory guide is essential reading for getting started with using XHTML, CSS and JavaScript to create exciting and compelling Web sites.Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

    When working hand-in-hand, they serve as the standard for the rapid development of dynamic, database-driven websites. This combination is so popular, in fact, that it's attracting manyprogramming newbies who come from a web or graphic design background and whose first language is HTML. If you fall into this ever-expanding category, then this book is for you."Learning PHP and MySQL" starts with the very basics of the PHP language, including strings and arrays, pattern matching and a detailed discussion of the variances in different PHP versions. Next, it explains how to work with MySQL, covering information on SQL data access for language and data fundamentals like tables and statements.Finally, after it's sure that you've mastered these separate concepts, the book shows you how to put them together to generate dynamic content. In the process, you'll also learn about error handling, security, HTTP authentication, and more.If you're a hobbyist who is intimidated by thick, complex computer books, then this guide definitely belongs on your shelf. "Learning PHP and MySQL" explains everything--from basic concepts to the nuts and bolts of performing specific tasks--in plain English.Part of O'Reilly's bestselling Learning series, the book is an easy-to-use resource designed specifically for newcomers. It's also a launching pad for future learning, providing you with a solid foundation for more advanced development.

    

    You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google

    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.

    It is suitable for a one or two semester university course on AI, as well as for researchers in the field.

     They are also used in countless industries such as medicine, manufacturing and finance to help companies make better decisions and reduce risk. Whether coded or scratched out by hand, both algorithms are powerful tools that can make a significant impact. This book is a visual introduction for beginners that unpacks the fundamentals of decision trees and random forests. If you want to dig into the basics with a visual twist plus create your own machine learning algorithms in Python, this book is for you.