However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    Building on their experience as professional systems analysts and award-winning teachers, authors Dennis, Wixom, and Roth capture the experience of developing and analyzing systems in a way that students can understand and apply.With Systems Analysis and Design, 4th edition , students will leave the course with experience that is a rich foundation for further work as a systems analyst.

    He asks the question: what makes high-achievers different?His answer is that we pay too much attention to what successful people are like, and too little attention to where they are from: that is, their culture, their family, their generation, and the idiosyncratic experiences of their upbringing. Along the way he explains the secrets of software billionaires, what it takes to be a great soccer player, why Asians are good at math, and what made the Beatles the greatest rock band.Brilliant and entertaining, Outliers is a landmark work that will simultaneously delight and illuminate.

    Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior.How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions.It's time to start thinking big.In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate.Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.

    A results-only classroom is rich with individual and cooperative learning activities that help students demonstrate mastery learning on their own terms, without being constrained by standards and pedagogy.By embracing results-only learning, you will be able to transform your classroom into a bustling community of learners in which?* Students collaborate daily on a number of long-term, ongoing projects.* Students receive constant narrative feedback.* Yearlong projects target learning outcomes more meaningfully than worksheets, homework, tests, and quizzes.* Freedom and independence are valued over punitive points, percentages, and letter grades.* Students manage themselves and all but eliminate the need for traditional classroom management.Learn how your students can take charge of their own achievement in an enjoyable, project-based, workshop setting that challenges them with real-world learning scenarios--and helps them attain uncommonly excellent results.

    This book is both an example-driven programmer's guide and a keep-on-your-desk reference, with new chapters that explain everything you need to know to get the most out of JavaScript, including:Scripted HTTP and Ajax XML processing Client-side graphics using the canvas tag Namespaces in JavaScript--essential when writing complex programs Classes, closures, persistence, Flash, and JavaScript embedded in Java applicationsPart I explains the core JavaScript language in detail. If you are new to JavaScript, it will teach you the language. If you are already a JavaScript programmer, Part I will sharpen your skills and deepen your understanding of the language.Part II explains the scripting environment provided by web browsers, with a focus on DOM scripting with unobtrusive JavaScript. The broad and deep coverage of client-side JavaScript is illustrated with many sophisticated examples that demonstrate how to:Generate a table of contents for an HTML document Display DHTML animations Automate form validation Draw dynamic pie charts Make HTML elements draggable Define keyboard shortcuts for web applications Create Ajax-enabled tool tips Use XPath and XSLT on XML documents loaded with Ajax And much morePart III is a complete reference for core JavaScript. It documents every class, object, constructor, method, function, property, and constant defined by JavaScript 1.5 and ECMAScript Version 3.Part IV is a reference for client-side JavaScript, covering legacy web browser APIs, the standard Level 2 DOM API, and emerging standards such as the XMLHttpRequest object and the canvas tag.More than 300,000 JavaScript programmers around the world have made this their indispensable reference book for building JavaScript applications."A must-have reference for expert JavaScript programmers...well-organized and detailed."-- Brendan Eich, creator of JavaScript

    Looks at the role of emotional intelligence in leadership, discussing the characteristics of a good leader and leadership styles, and outlines the steps to becoming an effective leader.

      Equally useful and entertaining, The Asshole Survival Guide delivers a cogent and methodical game plan when you find yourself working with a jerk—whether in the office, on the field, in the classroom, or just in life.     Sutton starts with diagnosis—what kind of asshole problem, exactly, are you dealing with? From there, he provides field-tested, evidence-based, and sometimes surprising strategies for dealing with the rude, impolite, irritating, unpleasant, or just plain incompetent—avoiding them, outwitting them, disarming them, sending them packing, and developing protective psychological armor. Sutton even teaches readers how to look inward to stifle their own inner jackass. 
  
   Ultimately, this survival guide is about developing an outlook and personal plan that will help you preserve the sanity in your life, and will prevent all those perfectly good days from being ruined by some jerk.

    If you're working with a relational database--whether you're writing applications, performing administrative tasks, or generating reports--you need to know how to interact with your data. Even if you are using a tool that generates SQL for you, such as a reporting tool, there may still be cases where you need to bypass the automatic generation feature and write your own SQL statements.To help you attain this fundamental SQL knowledge, look to "Learning SQL," an introductory guide to SQL, designed primarily for developers just cutting their teeth on the language."Learning SQL" moves you quickly through the basics and then on to some of the more commonly used advanced features. Among the topics discussed: The history of the computerized databaseSQL Data Statements--those used to create, manipulate, and retrieve data stored in your database; example statements include select, update, insert, and deleteSQL Schema Statements--those used to create database objects, such as tables, indexes, and constraintsHow data sets can interact with queriesThe importance of subqueriesData conversion and manipulation via SQL's built-in functionsHow conditional logic can be used in Data StatementsBest of all, "Learning SQL" talks to you in a real-world manner, discussing various platform differences that you're likely to encounter and offering a series of chapter exercises that walk you through the learning process. Whenever possible, the book sticks to the features included in the ANSI SQL standards. This means you'll be able to apply what you learn to any of several different databases; the book covers MySQL, Microsoft SQL Server, and Oracle Database, but the features and syntax should apply just as well (perhaps with some tweaking) to IBM DB2, Sybase Adaptive Server, and PostgreSQL.Put the power and flexibility of SQL to work. With "Learning SQL" you can master this important skill and know that the SQL statements you write are indeed correct.

    The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it.In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go.Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

    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

    Writing is hard work and can be difficult to wedge into a frenetic academic schedule.This revised and updated edition of Paul Silvia's popular guide provides practical, light-hearted advice to help academics overcome common barriers and become productive writers. Silvia's expert tips have been updated to apply to a wide variety of disciplines, and this edition has a new chapter devoted to grant and fellowship writing.

    The SY0-301 version covers every aspect of the SY0-301 exam, and includes the same elements readers raved about in the previous version. Each of the eleven chapters presents topics in an easy to understand manner and includes real-world examples of security principles in action. The author uses many of the same analogies and explanations he's honed in the classroom that have helped hundreds of students master the Security+ content. You'll understand the important and relevant security topics for the Security+ exam, without being overloaded with unnecessary details. Additionally, each chapter includes a comprehensive review section to help you focus on what's important. Over 450 realistic practice test questions with in-depth explanations will help you test your comprehension and readiness for the exam. The book includes a 100 question pre-test, a 100 question post-test, and practice test questions at the end of every chapter. Each practice test question includes a detailed explanation to help you understand the content and the reasoning behind the question. You'll be ready to take and pass the exam the first time you take it. If you plan to pursue any of the advanced security certifications, this guide will also help you lay a solid foundation of security knowledge. Learn this material, and you'll be a step ahead for other exams. This SY0-301 study guide is for any IT or security professional interested in advancing in their field, and a must read for anyone striving to master the basics of IT systems security. The author supplements the book with blog posts here: http: //blogs.getcertifiedgetahead.com/. This page provides a full listing of mobile device apps from the author: http: //learnzapp.com/partners/darrilgibson/

    Over the years sports debates have become muddled by many myths that do not match the numbers generated by those playing the games. In The Wages of Wins, the authors use layman's language and easy to follow examples based on their own academic research to debunk many of the most commonly held beliefs about sports.In this updated version of their book, these authors explain why Allen Iverson leaving Philadelphia made the 76ers a better team, why the Yankees find it so hard to repeat their success from the late 1990s, and why even great quarterbacks like Brett Favre are consistently inconsistent. The book names names, and makes it abundantly clear that much of the decision making of coaches and general managers does not hold up to an analysis of the numbers. Whether you are a fantasy league fanatic or a casual weekend fan, much of what you believe about sports will change after reading this book.

    Bannon had long sensed that deep within America's soul lurked an explosive tension. Cambridge Analytica had the data to prove it, and in 2016 Bannon had a presidential campaign to use as his proving ground.Christopher Wylie might have seemed an unlikely figure to be at the center of such an operation. Canadian and liberal in his politics, he was only twenty-four when he got a job with a London firm that worked with the U.K. Ministry of Defense and was charged putatively with helping to build a team of data scientists to create new tools to identify and combat radical extremism online. In short order, those same military tools were turned to political purposes, and Cambridge Analytica was born. Wylie's decision to become a whistleblower prompted the largest data crime investigation in history. His story is both exposé and dire warning about a sudden problem born of very new and powerful capabilities. It has not only exposed the profound vulnerabilities and profound carelessness in the enormous companies that drive the attention economy, it has also exposed the profound vulnerabilities of democracy itself. What happened in 2016 was just a trial run. Ruthless actors are coming for your data, and they want to control what you think.