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.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    It also works beautifully with other open source tools, such as the MySQL database and the Apache web server. However, as more web sites are developed in PHP, they become targets for malicious attackers, and developers need to prepare for the attacks.Security is an issue that demands attention, given the growing frequency of attacks on web sites. Essential PHP Security explains the most common types of attacks and how to write code that isn't susceptible to them. By examining specific attacks and the techniques used to protect against them, you will have a deeper understanding and appreciation of the safeguards you are about to learn in this book.In the much-needed (and highly-requested) Essential PHP Security, each chapter covers an aspect of a web application (such as form processing, database programming, session management, and authentication). Chapters describe potential attacks with examples and then explain techniques to help you prevent those attacks.Topics covered include:Preventing cross-site scripting (XSS) vulnerabilitiesProtecting against SQL injection attacksComplicating session hijacking attemptsYou are in good hands with author Chris Shiflett, an internationally-recognized expert in the field of PHP security. Shiflett is also the founder and President of Brain Bulb, a PHP consultancy that offers a variety of services to clients around the world.

    Book annotation not available for this title.Title: CCNP ROUTE 642-902Author: Odom, WendellPublisher: Pearson P T RPublication Date: 2010/02/09Number of Pages: 730Binding Type: HARDCOVERLibrary of Congress: 2009049908

    

    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!

    And learning these idioms and phrases will not only help you speak English better, it'll help you understand Americans better!Idioms are presented in 25 lively dialogues which tell the entertaining story of an American family, complete with illustrations. The book comes with an audio CD of all of the dialogues. Contains dozens of helpful exercises & six crossword puzzles to reinforce the material, with convenient answer key for self-study. About the AuthorAmy Gillett has taught ESL (English as a Second Language) in both the United States and Europe. She holds a BA degree in literature fromStanford University, an MA from Stanford in Russian & East European Studies, and an MBA from Cornell. She speaks several foreign languages.Her writing has appeared in many national magazines and newspapers, including MAD Magazine, Family Circle, and the San Francisco Chronicle.

    This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9

    It’s helpful for learning Agile and Scrum, and also for a basic preparation for the PSM I exam (Professional Scrum Master level 1). It can also act as a simple reference for Scrum practitioners.

    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.

    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

    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)

    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

    Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.

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