This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

    Due to their monopoly position in web browsers, and the fact web browsers have spread from PCs to phones, tablets and TVs; their status will continue to grow and grow. Despite their success, many software engineers are apprehensive about JavaScript and HTML. This apprehensiveness is not completely unfounded; both JavaScript and HTML were rushed in their early years, and driven by commercial rather than engineering interests. As a result, many dubious features crept into these languages. Due to backwards compatibility concerns, most of these features still remain. In addition, many software engineers have used these languages without ever learning them. JavaScript and HTML have low barriers to entry, and this, along with their similarity to other languages, led many software engineers to conclude that there really was nothing much to learn. If you have not used JavaScript and HTML for a number of years, or if you are a programmer or software engineer using other languages, you may be surprised at what they now offer. Browser based web applications are now capable of matching or exceeding the sophistication and scale of traditional desktop applications. In order to create complex web applications however, it is essential to learn these languages. This book takes the point of view that once you have a strong grasp of the fundamentals, the details will take care of themselves. It will not present you with long lists of APIs, or intricate details of every attribute, these can be found in reference manuals. It will focus on the details of each language that are fundamental to understanding how they work. This book will guide you through the process of developing a web application using HTML5, Javascript, jQuery and CSS. It contains the following content: 1. An introduction to the HTML5 markup language, and how it differs from HTML4 and XHTML. 2. An introduction to JavaScript, including an in-depth look at its use of objects and functions, along with the design patterns that support the development of robust web applications. 3. An introduction to jQuery selection, traversal, manipulation and events. 4. An in-depth look at the Web storage and IndexedDB APIs for client side data storage. 5. A guide to implementing offline web applications with the Application Cache API. 6. An introduction to the ways JavaScript can interact with the users file-system using the FileReader API. 7. The use of Web Workers in a web application to execute algorithms on background threads. 8. An introduction to AJAX, and the jQuery API supporting AJAX. 9. An introduction to Server Sent Events and Web Sockets. All subjects are introduced in the context of a sample web application. This book is intended for anyone with at least a superficial knowledge of HTML and programming.

    Distinct from the details of implementation, algorithm, and data representation, an architecture holds the key to achieving system quality, is a reusable asset that can be applied to subsequent systems, and is crucial to a software organization's business strategy.Drawing on their own extensive experience, the authors cover the essential technical topics for designing, specifying, and validating a system. They also emphasize the importance of the business context in which large systems are designed. Their aim is to present software architecture in a real-world setting, reflecting both the opportunities and constraints that companies encounter. To that end, case studies that describe successful architectures illustrate key points of both technical and organizational discussions.Topics new to this edition include: Architecture design and analysis, including the Architecture Tradeoff Analysis Method (ATAM) Capturing quality requirements and achieving them through quality scenarios and tactics Using architecture reconstruction to recover undocumented architectures Documenting architectures using the Unified Modeling Language (UML) New case studies, including Web-based examples and a wireless Enterprise JavaBeans™ (EJB) system designed to support wearable computers The financial aspects of architectures, including use of the Cost Benefit Analysis Method (CBAM) to make decisions If you design, develop, or manage the building of large software systems (or plan to do so), or if you are interested in acquiring such systems for your corporation or government agency, use Software Architecture in Practice, Second Edition, to get up to speed on the current state of software architecture.

    R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community

    Packed with examples and helpful recommendations, the book has helped everyone--from novices to experienced developers, and from Oracle Forms developers to database administrators--make the most of PL/SQL. The fourth edition is a comprehensive update, adding significant new content and extending coverage to include the very latest Oracle version, Oracle Database 10g Release 2. It describes such new features as the PL/SQL optimizing compiler, conditional compilation, compile-time warnings, regular expressions, set operators for nested tables, nonsequential collections in FORALL, the programmer-defined quoting mechanism, the ability to backtrace an exception to a line number, a variety of new built-in packages, and support for IEEE 754 compliant floating-point numbers. The new edition adds brand-new chapters on security (including encryption, row-level security, fine-grained auditing, and application contexts), file, email, and web I/O (including the built-in packages DBMS_OUTPUT, UTL_FILE, UTL_MAIL, UTL_SMTP, and UTL_HTTP) and globalization and localization. Co-authored by the world's foremost PL/SQL authority, Steven Feuerstein, this classic reference provides language syntax, best practices, and extensive code, ranging from simple examples to complete applications--making it a must-have on your road to PL/SQL mastery. A companion web site contains many more examples and additional technical content for enhanced learning.

    You'll also receive updates when significant changes are made, as well as the final ebook version. Embedded Android is for Developers wanting to create embedded systems based on Android and for those wanting to port Android to new hardware, or creating a custom development environment. Hackers and moders will also find this an indispensible guide to how Android works.

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    Now he's sharing his collection of antipatterns--the most common errors he's identified in those thousands of requests for help. Most developers aren't SQL experts, and most of the SQL that gets used is inefficient, hard to maintain, and sometimes just plain wrong. This book shows you all the common mistakes, and then leads you through the best fixes. What's more, it shows you what's behind these fixes, so you'll learn a lot about relational databases along the way. Each chapter in this book helps you identify, explain, and correct a unique and dangerous antipattern. The four parts of the book group the anti​patterns in terms of logical database design, physical database design, queries, and application development. The chances are good that your application's database layer already contains problems such as Index Shotgun, Keyless Entry, Fear of the Unknown, and Spaghetti Query. This book will help you and your team find them. Even better, it will also show you how to fix them, and how to avoid these and other problems in the future. SQL Antipatterns gives you a rare glimpse into an SQL expert's playbook. Now you can stamp out these common database errors once and for all. Whatever platform or programming language you use, whether you're a junior programmer or a Ph.D., SQL Antipatterns will show you how to design and build databases, how to write better database queries, and how to integrate SQL programming with your application like an expert. You'll also learn the best and most current technology for full-text search, how to design code that is resistant to SQL injection attacks, and other techniques for success.

    This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

    Some books try to give you copy-and-paste instructions for how to deal with every single system issue that may arise, but How Linux Works actually shows you how the Linux system functions so that you can come up with your own solutions. After a guided tour of filesystems, the boot sequence, system management basics, and networking, author Brian Ward delves into open-ended topics such as development tools, custom kernels, and buying hardware, all from an administrator's point of view. With a mixture of background theory and real-world examples, this book shows both "how" to administer Linux, and "why" each particular technique works, so that you will know how to make Linux work for you.

    

    In this book, you'll learn how to become an entrepreneur, driving your career in the direction of your choosing. You'll learn how to build your software development career step by step, following the same path that you would follow if you were building, marketing, and selling a product. After all, your skills themselves are a product. The choices you make about which technologies to focus on and which business domains to master have at least as much impact on your success as your technical knowledge itself--don't let those choices be accidental. We'll walk through all aspects of the decision-making process, so you can ensure that you're investing your time and energy in the right areas. You'll develop a structured plan for keeping your mind engaged and your skills fresh. You'll learn how to assess your skills in terms of where they fit on the value chain, driving you away from commodity skills and toward those that are in high demand. Through a mix of high-level, thought-provoking essays and tactical "Act on It" sections, you will come away with concrete plans you can put into action immediately. You'll also get a chance to read the perspectives of several highly successful members of our industry from a variety of career paths. As with any product or service, if nobody knows what you're selling, nobody will buy. We'll walk through the often-neglected world of marketing, and you'll create a plan to market yourself both inside your company and to the industry in general. Above all, you'll see how you can set the direction of your career, leading to a more fulfilling and remarkable professional life.

    This 4-book set includes:Professional JavaScript for Web Developers (ISBN: 0764579088) Professional Ajax 2nd edition (ISBN: 0470109491) Professional Web 2.0 Programming (ISBN: 0470087889) Professional Rich Internet Applications: Ajax and Beyond (ISBN: 0470082801)

    R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http: //www.imperial.ac.uk/bio/research/crawl... Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.