But, although they use these patterns purposefully, they often use them informally and nearly unconsciously. This book organizes this substantial emerging "folklore" of system design -- with its rich language of system description -- and closes the gap between the useful abstractions (constructs and patterns) of system design and the current models, notations and tools. It identifies useful patterns clearly, gives examples, compares them, and evaluates their utility in various settings -- allowing readers to develop a repertoire of useful techniques that goes beyond the single-minded current fads. KEY TOPICS: Examines the ways in which architectural issues can impact software design; shows how to design new systems in principled ways using well-understood architectural paradigms; emphasizes informal descriptions, touching lightly on formal notations and specifications, and the tools that support them; explains how to understand and evaluate the design of existing software systems from an architectural perspective; and presents concrete examples of actual system architectures that can serve as models for new designs. MARKET: For professional software developers looking for new ideas about system organization.

    The data world was revolutionized a few years ago when Hadoop and other tools made it possible to getthe results from queries in minutes. But the revolution continues. Analysts now demand sub-second, near real-time query results. Fortunately, we have the tools to deliver them. This report examines tools and technologies that are driving real-time big data analytics.

    The result is described as “a thought-provoking visual feast”.

    By staying current, remaining relevant, and adapting to emerging course needs, this market-leading text has continued to define the operating systems course. This Seventh Edition not only presents the latest and most relevant systems, it also digs deeper to uncover those fundamental concepts that have remained constant throughout the evolution of today's operation systems. With this strong conceptual foundation in place, students can more easily understand the details related to specific systems. New Adaptations * Increased coverage of user perspective in Chapter 1. * Increased coverage of OS design throughout. * A new chapter on real-time and embedded systems (Chapter 19). * A new chapter on multimedia (Chapter 20). * Additional coverage of security and protection. * Additional coverage of distributed programming. * New exercises at the end of each chapter. * New programming exercises and projects at the end of each chapter. * New student-focused pedagogy and a new two-color design to enhance the learning process.

    

    Throughout, the emphasis is on how IT provides organizations with strategic advantage by facilitating problem solving, increasing productivity and quality, improving customer service, and enabling business process reengineering. It also covers the latest real-world developments, including the introduction of applied grid computing and utility computing.

    They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Consequently, organizations that understand these tools and know how to use them are benefiting at the expense of their rivals.Artificial Intelligence and Machine Learning for Business cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies.This revised and fully updated edition contains several new sections and chapters, covering a broader set of topics than before, but retains the no-nonsense style of the original.Steven Finlay is a data scientist and author with more than 20 years’ experience of developing practical, business focused, analytical solutions. He holds a PhD in management science and is an honorary research fellow at Lancaster University in the UK.

    This book serves as the first guide to focus on combining the benefits of balanced scorecards, operational dashboards, performance managements, and data visualization and then implement them in Microsoft Excel.

    Part tutorial and part reference, the book serves as a learning tool for building new JavaScript skills and a detailed reference for seasoned JavaScript developers. Danny Goodman's exclusive interactive workbench, The Evaluator, makes it easy to master JavaScript and DOM concepts. Offers deployment strategies that best suit the user's content goals and target audience.Bonus CD-ROM is packed with advanced content for the reader who wants to go an extra step.

    AIQ explores the fascinating history of the ideas that drive this technology of the future and demystifies the core concepts behind it; the result is a positive and entertaining look at the great potential unlocked by marrying human creativity with powerful machines.” —Steven D. Levitt, bestselling co-author of Freakonomics From leading data scientists Nick Polson and James Scott, what everyone needs to know to understand how artificial intelligence is changing the world and how we can use this knowledge to make better decisions in our own lives. Dozens of times per day, we all interact with intelligent machines that are constantly learning from the wealth of data now available to them. These machines, from smart phones to talking robots to self-driving cars, are remaking the world in the 21st century in the same way that the Industrial Revolution remade the world in the 19th century. AIQ is based on a simple premise: if you want to understand the modern world, then you have to know a little bit of the mathematical language spoken by intelligent machines. AIQ will teach you that language—but in an unconventional way, anchored in stories rather than equations. You will meet a fascinating cast of historical characters who have a lot to teach you about data, probability, and better thinking. Along the way, you'll see how these same ideas are playing out in the modern age of big data and intelligent machines—and how these technologies will soon help you to overcome some of your built-in cognitive weaknesses, giving you a chance to lead a happier, healthier, more fulfilled life.

    With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Spark’s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

    I loved the tutorial-style game-like program development. This book rekindled my earliest joys of programming. Plus, JavaScript!" —Brendan Eich, creator of JavaScriptJavaScript is the language of the Web, and it's at the heart of every modern website from the lowliest personal blog to the mighty Google Apps. Though it's simple for beginners to pick up and play with, JavaScript is not a toy—it's a flexible and complex language, capable of much more than the showy tricks most programmers use it for.Eloquent JavaScript goes beyond the cut-and-paste scripts of the recipe books and teaches you to write code that's elegant and effective. You'll start with the basics of programming, and learn to use variables, control structures, functions, and data structures. Then you'll dive into the real JavaScript artistry: higher-order functions, closures, and object-oriented programming.Along the way you'll learn to:Master basic programming techniques and best practices Harness the power of functional and object-oriented programming Use regular expressions to quickly parse and manipulate strings Gracefully deal with errors and browser incompatibilities Handle browser events and alter the DOM structure Most importantly, Eloquent JavaScript will teach you to express yourself in code with precision and beauty. After all, great programming is an art, not a science—so why settle for a killer app when you can create a masterpiece?

    This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to - Use the scientific method to evaluate hypotheses using controlled experiments - Define key metrics and ideally an Overall Evaluation Criterion - Test for trustworthiness of the results and alert experimenters to violated assumptions - Build a scalable platform that lowers the marginal cost of experiments close to zero - Avoid pitfalls like carryover effects and Twyman's law - Understand how statistical issues play out in practice.

    Kai-Fu Lee—one of the world’s most respected experts on AI and China—reveals that China has suddenly caught up to the US at an astonishingly rapid and unexpected pace.In AI Superpowers, Kai-Fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power.Most experts already say that AI will have a devastating impact on blue-collar jobs. But Lee predicts that Chinese and American AI will have a strong impact on white-collar jobs as well. Is universal basic income the solution? In Lee’s opinion, probably not.  But he provides a clear description of which jobs will be affected and how soon, which jobs can be enhanced with AI, and most importantly, how we can provide solutions to some of the most profound changes in human history that are coming soon.

    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