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

    The book details the major subsystems and features of the Linux kernel, including its design, implementation, and interfaces. It covers the Linux kernel with both a practical and theoretical eye, which should appeal to readers with a variety of interests and needs. The author, a core kernel developer, shares valuable knowledge and experience on the 2.6 Linux kernel. Specific topics covered include process management, scheduling, time management and timers, the system call interface, memory addressing, memory management, the page cache, the VFS, kernel synchronization, portability concerns, and debugging techniques. This book covers the most interesting features of the Linux 2.6 kernel, including the CFS scheduler, preemptive kernel, block I/O layer, and I/O schedulers. The third edition of Linux Kernel Development includes new and updated material throughout the book:An all-new chapter on kernel data structuresDetails on interrupt handlers and bottom halvesExtended coverage of virtual memory and memory allocationTips on debugging the Linux kernelIn-depth coverage of kernel synchronization and lockingUseful insight into submitting kernel patches and working with the Linux kernel community

    Built for your brain, this book covers C# 3.0 and Visual Studio 2008, and teaches everything from language fundamentals to advanced topics including garbage collection, extension methods, and double-buffered animation. You'll also master C#'s hottest and newest syntax, LINQ, for querying SQL databases, .NET collections, and XML documents. By the time you're through, you'll be a proficient C# programmer, designing and coding large-scale applications. Every few chapters you will come across a lab that lets you apply what you've learned up to that point. Each lab is designed to simulate a professional programming task, increasing in complexity until-at last-you build a working Invaders game, complete with shooting ships, aliens descending while firing, and an animated death sequence for unlucky starfighters. This remarkably engaging book will have you going from zero to 60 with C# in no time flat.

    Stallings presents the nature and characteristics of modern-day operating systems clearly and completely.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    Isn't it time you learned the latest (J2EE 1.4) versions of Servlets & JSPs? This book will get you way up to speed on the technology you'll know it so well, in fact, that you can pass the Sun Certified Web Component Developer (SCWCD) 1.4 exam. If that's what you want to do, that is. Maybe you don't care about the exam, but need to use Servlets & JSPs in your next project. You're working on a deadline. You're over the legal limit for caffeine. You can't waste your time with a book that makes sense only AFTER you're an expert (or worse one that puts you to sleep). No problem. Head First Servlets and JSP's brain-friendly approach drives the knowledge straight into your head (without sharp instruments). You'll interact with servlets and JSPs in ways that help you learn quickly and deeply. It may not be The Da Vinci Code, but quickly see why so many reviewers call it "a page turner". Most importantly, this book will help you use what you learn. It won't get you through the exam only to have you forget everything the next day. Learn to write servlets and JSPs, what makes the Container tick (and what ticks it off), how to use the new JSP Expression Language (EL), what you should NOT write in a JSP, how to write deployment descriptors, secure applications, and even use some server-side design patterns. Can't talk about Struts at a cocktail party? That'll change. You won't just pass the exam, you will truly understand this stuff, and you'll be able to put it to work right away. This new exam is tough--much tougher than the previous version of the SCWCD. The authors of Head First Servlets and JSP know: they created it. (Not that it EVER occurred to them that if they made the exam really hard you'd have to buy a study guide to pass it.) The least they could do is give you a stimulating, fun way to pass the thing. If you're one of the thousands who used Head First EJB to pass the SCWCD exam, you know what to expect!

    You thought TDD was for someone else, but it's not! It's for you, the embedded C programmer. TDD helps you prevent defects and build software with a long useful life. This is the first book to teach the hows and whys of TDD for C programmers. TDD is a modern programming practice C developers need to know. It's a different way to program---unit tests are written in a tight feedback loop with the production code, assuring your code does what you think. You get valuable feedback every few minutes. You find mistakes before they become bugs. You get early warning of design problems. You get immediate notification of side effect defects. You get to spend more time adding valuable features to your product. James is one of the few experts in applying TDD to embedded C. With his 1.5 decades of training, coaching, and practicing TDD in C, C++, Java, and C# he will lead you from being a novice in TDD to using the techniques that few have mastered. This book is full of code written for embedded C programmers. You don't just see the end product, you see code and tests evolve. James leads you through the thought process and decisions made each step of the way. You'll learn techniques for test-driving code right next to the hardware, and you'll learn design principles and how to apply them to C to keep your code clean and flexible. To run the examples in this book, you will need a C/C++ development environment on your machine, and the GNU GCC tool chain or Microsoft Visual Studio for C++ (some project conversion may be needed).

    This book provides information on software tools, specific work flow for specific kinds of projects, and information on various topics. It includes resources for both instructors and students such as checklists, 700 categorized web references, and more.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    The authors are well-known for their clear presentation that makes the material accessible to a a broad audience and requires no special previous mathematical experience. KEY TOPICS: In this new edition, the authors incorporate a somewhat more informal, friendly writing style to present both classical and contemporary theories of computation. Algorithms, complexity analysis, and algorithmic ideas are introduced informally in Chapter 1, and are pursued throughout the book. Each section is followed by problems.

    Along the way, we encounter black holes, turtles, snakes, dragons, axe-sharpening, and yak-shaving—and take a guided tour through the theories and methods, both brilliant and misguided, that litter the history of software development, from the famous ‘mythical man-month’ to Extreme Programming. Not just for technophiles but for anyone captivated by the drama of invention, Dreaming in Code offers a window into both the information age and the workings of the human mind.

    This is a hands-on guide to mastering Objective C - the language every MAC OS X and iPhone/iPod Touch developer needs to know.

    It's used worldwide by companies who need to produce reliable, efficient, and scalable applications. Invest in learning Erlang now.Moore's Law is the observation that the amount you can do on a single chip doubles every two years. But Moore's Law is taking a detour. Rather than producing faster and faster processors, companies such as Intel and AMD are producing multi-core devices: single chips containing two, four, or more processors. If your programs aren't concurrent, they'll only run on a single processor at a time. Your users will think that your code is slow.Erlang is a programming language designed for building highly parallel, distributed, fault-tolerant systems. It has been used commercially for many years to build massive fault-tolerated systems that run for years with minimal failures.Erlang programs run seamlessly on multi-core computers: this means your Erlang program should run a lot faster on a 4 core processor than on a single core processor, all without you having to change a line of code.Erlang combines ideas from the world of functional programming with techniques for building fault-tolerant systems to make a powerful language for building the massively parallel, networked applications of the future.This book presents Erlang and functional programming in the familiar Pragmatic style. And it's written by Joe Armstrong, one of the creators of Erlang.It includes example code you'll be able to build upon. In addition, the book contains the full source code for two interesting applications:A SHOUTcast server which you can use to stream music to every computer in your house, and a full-text indexing and search engine that can index gigabytes of data. Learn how to write programs that run on dozens or even hundreds of local and remote processors. See how to write robust applications that run even in the face of network and hardware failure, using the Erlang programming language.

    It's the expertise you need when your start-up gets an unexpected spike in web traffic, or when a new feature causes your mature application to fail. In this collection of essays and interviews, web veterans such as Theo Schlossnagle, Baron Schwartz, and Alistair Croll offer insights into this evolving field. You'll learn stories from the trenches--from builders of some of the biggest sites on the Web--on what's necessary to help a site thrive.Learn the skills needed in web operations, and why they're gained through experience rather than schoolingUnderstand why it's important to gather metrics from both your application and infrastructureConsider common approaches to database architectures and the pitfalls that come with increasing scaleLearn how to handle the human side of outages and degradationsFind out how one company avoided disaster after a huge traffic delugeDiscover what went wrong after a problem occurs, and how to prevent it from happening againContributors include:John AllspawHeather ChampMichael ChristianRichard CookAlistair CrollPatrick DeboisEric FlorenzanoPaul HammondJustin HuffAdam JacobJacob LoomisMatt MassieBrian MoonAnoop NagwaniSean PowerEric RiesTheo SchlossnagleBaron SchwartzAndrew Shafer

    By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.