These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    Tracy Kidder got a preview of this world in the late 1970s when he observed the engineers of Data General design and build a new 32-bit minicomputer in just one year. His thoughtful, prescient book, The Soul of a New Machine, tells stories of 35-year-old "veteran" engineers hiring recent college graduates and encouraging them to work harder and faster on complex and difficult projects, exploiting the youngsters' ignorance of normal scheduling processes while engendering a new kind of work ethic.These days, we are used to the "total commitment" philosophy of managing technical creation, but Kidder was surprised and even a little alarmed at the obsessions and compulsions he found. From in-house political struggles to workers being permitted to tease management to marathon 24-hour work sessions, The Soul of a New Machine explores concepts that already seem familiar, even old-hat, less than 20 years later. Kidder plainly admires his subjects; while he admits to hopeless confusion about their work, he finds their dedication heroic. The reader wonders, though, what will become of it all, now and in the future. —Rob Lightner

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    Displaying extraordinary creativity and programming virtuosity, Alexandrescu offers a cutting-edge approach to design that unites design patterns, generic programming, and C++, enabling programmers to achieve expressive, flexible, and highly reusable code. This book introduces the concept of generic components--reusable design templates that produce boilerplate code for compiler consumption--all within C++. Generic components enable an easier and more seamless transition from design to application code, generate code that better expresses the original design intention, and support the reuse of design structures with minimal recoding. The author describes the specific C++ techniques and features that are used in building generic components and goes on to implement industrial strength generic components for real-world applications. Recurring issues that C++ developers face in their day-to-day activity are discussed in depth and implemented in a generic way. These include: Policy-based design for flexibility Partial template specialization Typelists--powerful type manipulation structures Patterns such as Visitor, Singleton, Command, and Factories Multi-method engines For each generic component, the book presents the fundamental problems and design options, and finally implements a generic solution.

    The kernel handles all interactions between the CPU and the external world, and determines which programs will share processor time, in what order. It manages limited memory so well that hundreds of processes can share the system efficiently, and expertly organizes data transfers so that the CPU isn't kept waiting any longer than necessary for the relatively slow disks.The third edition of Understanding the Linux Kernel takes you on a guided tour of the most significant data structures, algorithms, and programming tricks used in the kernel. Probing beyond superficial features, the authors offer valuable insights to people who want to know how things really work inside their machine. Important Intel-specific features are discussed. Relevant segments of code are dissected line by line. But the book covers more than just the functioning of the code; it explains the theoretical underpinnings of why Linux does things the way it does.This edition of the book covers Version 2.6, which has seen significant changes to nearly every kernel subsystem, particularly in the areas of memory management and block devices. The book focuses on the following topics:Memory management, including file buffering, process swapping, and Direct memory Access (DMA)The Virtual Filesystem layer and the Second and Third Extended FilesystemsProcess creation and schedulingSignals, interrupts, and the essential interfaces to device driversTimingSynchronization within the kernelInterprocess Communication (IPC)Program executionUnderstanding the Linux Kernel will acquaint you with all the inner workings of Linux, but it's more than just an academic exercise. You'll learn what conditions bring out Linux's best performance, and you'll see how it meets the challenge of providing good system response during process scheduling, file access, and memory management in a wide variety of environments. This book will help you make the most of your Linux system.

    The aim of The Node Beginner Book is to get you started with developing applications for Node.js, teaching you everything you need to know about advanced JavaScript along the way on 59 pages.

    Today, Rails developers and architects need better ways to interface with legacy systems, move into the cloud, and scale to handle higher volumes and greater complexity. In Service-Oriented Design with Ruby and Rails Paul Dix introduces a powerful, services-based design approach geared toward overcoming all these challenges. Using Dix's techniques, readers can leverage the full benefits of both Ruby and Rails, while overcoming the difficulties of working with larger codebases and teams. Dix demonstrates how to integrate multiple components within an enterprise application stack; create services that can easily grow and connect; and design systems that are easier to maintain and upgrade. Key concepts are explained with detailed Ruby code built using open source libraries such as ActiveRecord, Sinatra, Nokogiri, and Typhoeus. The book concludes with coverage of security, scaling, messaging, and interfacing with third-party services. Service-Oriented Design with Ruby and Rails will help you Build highly scalable, Ruby-based service architectures that operate smoothly in the cloud or with legacy systems Scale Rails systems to handle more requests, larger development teams, and more complex code bases Master new best practices for designing and creating services in Ruby Use Ruby to glue together services written in any language Use Ruby libraries to build and consume RESTful Web services Use Ruby JSON parsers to quickly represent resources from HTTP services Write lightweight, well-designed API wrappers around internal or external services Discover powerful non-Rails frameworks that simplify Ruby service implementation Implement standards-based enterprise messaging with Advanced Message Queuing Protocol (AMQP) Optimize performance with load balancing and caching Provide for security and authentication

    Topics are broken down into three major conceptual pieces: Virtualization, Concurrency, and Persistence. Includes all major components of modern systems including scheduling, virtual memory management, disk subsystems and I/O, file systems, and even a short introduction to distributed systems.

    While explaining key design decisions, it details the concepts, data structures, and algorithms used in implementing the systems facilities. It is both a practical reference and an in-depth study of a contemporary, portable, open source operating system.

    Through concrete examples and jargon-free explanations, this book teaches you how to apply functional programming to real-life development tasks. The book includes insightful comparisons to object-oriented or imperative programming, which will allow you to ease into functional design. Moreover, you'll learn a repertoire of techniques including function chaining and pipelining, recursion, currying, binding, functional composition, lazy evaluation, fluent error handling, memoization, and much more. By the end of the book, you'll think about application design in a fresh new way.About the technologyAs web developers build increasingly complex applications in JavaScript, the code base for these projects can become exponentially larger and harder to maintain. The result? Application performance suffers, and readability and extensibility are severely compromised. For applications like these, Functional Programming provides a saner approach, allowing you to write elegant, readable code that raises the level of abstraction while being less prone to errors. Although not a "pure" functional language, JavaScript's native functional capabilities unlock access to proven functional programming techniques and practices.What's insideFoundations of functional programming and designExplore JavaScript's functional programming capabilities and the functional library ecosystemCreate more reliable code by embracing immutabilityLearn to write code that's easier to reason aboutSeparate core logic from program structure to write extensible codeAdopt a new approach to error handling and testingApply functional programming to solve real-world problemsAbout the readerReaders need to be comfortable with JavaScript programming and object-oriented design. No previous experience with functional programming is required.About the authorLuis Atencio is a Staff Software Engineer for Citrix Systems in Ft. Lauderdale, FL. He develops and architects applications leveraging Java, PHP, and JavaScript platforms. Luis is very involved in the community and has presented at local meet-ups. He blogs about software engineering at luisatencio.net and writes articles for PHP magazines and DZone. Follow Luis on twitter at @luijar.

    This book will help the C programmer reach new heights as a professional. Organized to make it easy for the reader to scan to sections that are relevant to their immediate needs.

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    If you're an experienced developer looking to solve problems related to objects, functions, inheritance, and other language-specific categories, the abstractions and code templates in this guide are ideal -- whether you're writing a client-side, server-side, or desktop application with JavaScript.Written by JavaScript expert Stoyan Stefanov -- Senior Yahoo! Technical and architect of YSlow 2.0, the web page performance optimization tool -- JavaScript Patterns includes practical advice for implementing each pattern discussed, along with several hands-on examples. You'll also learn about anti-patterns: common programming approaches that cause more problems than they solve.Explore useful habits for writing high-quality JavaScript code, such as avoiding globals, using single var declarations, and moreLearn why literal notation patterns are simpler alternatives to constructor functionsDiscover different ways to define a function in JavaScriptCreate objects that go beyond the basic patterns of using object literals and constructor functionsLearn the options available for code reuse and inheritance in JavaScriptStudy sample JavaScript approaches to common design patterns such as Singleton, Factory, Decorator, and moreExamine patterns that apply specifically to the client-side browser environment

    In a very short amount of time, he is able to present an issue, fix it and conclude it; each chapter is tight, succinct, and to the point." --Josh Holmes, Independent Contractor "The book provides a good introduction to the C# language elements from a pragmatic point of view, identifying best practices along the way, and following a clear and logical progression from the basic syntax to creating components to improving your code writing skills. Since each topic is covered in short entries, it is very easy to read and you'll quickly realize the benefits of the book." --Tomas Restrepo, Microsoft MVP "The book covers the basics well, especially with respect to the decisions needed when deriving classes from System.Object. It is easy to read with examples that are clear, concise and solid. I think it will bring good value to most readers." --Rob Steel, Central Region Integration COE & Lead Architect, Microsoft "Effective C# provides the C# developer with the tools they need to rapidly grow their experience in Visual C# 2003 while also providing insight into the many improvements to the language that will be hitting a desktop near you in the form of Visual C# 2005." --Doug Holland, Precision Objects "Part of the point of the .NET Framework--and the C# Language, in particular--is to let the developer focus solving customer problems and deliver product, rather than spending hours (or even weeks) writing plumbing code. Bill Wagner's Effective C#, not only shows you what's going on behind the scenes, but shows you how to take advantage of particular C# code constructs. Written in a dispassionate style that focuses on the facts--and just the facts--of writing effective C# code, Wagner's book drills down into practices that will let you write C# applications and components that are easier to maintain as well as faster to run. I'm recommending Effective C# to all students of my .NET BootCamp and other C#-related courses." --Richard Hale Shaw, www.RichardHaleShawGroup.com C#'s resemblances to C++, Java, and C make it easier to learn, but there's a downside: C# programmers often continue to use older techniques when far better alternatives are available. In Effective C#, respected .NET expert Bill Wagner identifies fifty ways you can start leveraging the full power of C# in order to write faster, more efficient, and more reliable software. Effective C# follows the format that made Effective C++ (Addison-Wesley, 1998) and Effective Java (Addison-Wesley, 2001) indispensable to hundreds of thousands of developers: clear, practical explanations, expert tips, and plenty of realistic code examples. Drawing on his unsurpassed C# experience, Wagner addresses everything from value types to assemblies, exceptions to reflection. Along the way, he shows exactly how to avoid dozens of common C# performance and reliability pitfalls. You'll learn how to: Use both types of C# constants for efficiency and maintainability, see item 2 Use immutable data types to eliminate unnecessary error checking, see item 7 Avoid the C# function that'll practically always get you in trouble, see item 10 Minimize garbage collection, boxing, and unboxing, see items 16 and 17

    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.