You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation.Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data--Storytelling with Data will give you the skills and power to tell it!

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    . . . We need a good book in cyberethics to deal with the present and prepare us for an uncertain future. Tavani's Ethics and Technology is such a book." --from the foreword by James Moor, Dartmouth College Is there privacy in a world of camera phones and wireless networking? Does technology threaten your civil liberties? How will bioinformatics and nanotechnology affect us? Should you worry about equity and access in a globalized economy? From privacy and security to free speech and intellectual property to globalization and outsourcing, the issues and controversies of the information age are serious, complex, and pervasive. In this new edition of his groundbreaking book, Herman Tavani introduces computer professionals to the emerging field of Cyberethics, the interdisciplinary field of study that addresses these new ethical issues from all perspectives: technical, social, and philosophical. Using fascinating real-world examples--including the latest court decisions in such cases as Verizon v. RIAA, MGM v. Grokster, Google versus the Bush Administration, and the Children's Online Pornography Act (CIPA) --as well as hypothetical scenarios, he shows you how to understand and analyze the practical, moral, and legal issues that impact your work and your life. Tavani discusses such cutting-edge areas as: * Globalization and outsourcing * Property rights and open source software * HIPAA (privacy laws) and surveillance * The Patriot Act and civil liberties * Bioinformatics and genomics research * Converging technologies--pervasive computing and nanocomputing * Children's online pornography laws Updating and expanding upon the previous edition, Ethics and Technology, Second Edition provides a much-needed ethical compass to help computer and non-computer professionals alike navigate the challenging waters of cyberspace. About the Author Herman T. Tavani is Professor of Philosophy at Rivier College and Co-Director of the International Society for Ethics and Information Technology (INSEIT). He is the author, editor, or co-editor of five books on ethical aspects of information technology. www.wiley.com/college/tavani

    C++ Templates: The Complete Guide provides software architects and engineers with a clear understanding of why, when, and how to use templates to build and maintain cleaner, faster, and smarter software more efficiently. C++ Templates begins with an insightful tutorial on basic concepts and language features. The remainder of the book serves as a comprehensive reference, focusing first on language details, then on a wide range of coding techniques, and finally on advanced applications for templates. Examples used throughout the book illustrate abstract concepts and demonstrate best practices. Readers learn: The exact behaviors of templates How to avoid the pitfalls associated with templates Idioms and techniques, from the basic to the previously undocumented How to reuse source code without threatening performance or safety How to increase the efficiency of C++ programs How to produce more flexible and maintainable software This practical guide shows programmers how to exploit the full power of the template features in C++.

    Introducing students to the many facets of neural networks, this text provides many case studies to illustrate their real-life, practical applications.

    Author Caleb Doxsey covers the language’s core features with step-by-step instructions and exercises in each chapter to help you practice what you learn.Go is a general-purpose programming language with a clean syntax and advanced features, including concurrency. This book provides the one-on-one support you need to get started with the language, with short, easily digestible chapters that build on one another. By the time you finish this book, not only will you be able to write real Go programs, you'll be ready to tackle advanced techniques.* Jump into Go basics, including data types, variables, and control structures* Learn complex types, such as slices, functions, structs, and interfaces* Explore Go’s core library and learn how to create your own package* Write tests for your code by using the language’s go test program* Learn how to run programs concurrently with goroutines and channels* Get suggestions to help you master the craft of programming

    Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    Salesforce.com (more than 50%) and Twitter (more than 75% fall into this category. Ebay gets more than 8 billion API calls a month. Facebook and Google, have dozens of APIs that enable both free services and e-commerce, get more than 5 billion API calls each day. Other companies like NetFlix have expanded their service of streaming movies over the the web to dozens of devices using API. At peak times, more than 20 percent of all traffic is accounted for by Netflix through its APIs. Companies like Sears and E-Trade are opening up their catalogs and other services to allow developers and entrepreneurs to create new marketing experiences. Making an API work to create a new channel is not just a matter of technology. An API must be considered in terms of business strategy, marketing, and operations as well as the technical aspects of programming. This book, written by Greg Brail, CTO of Apigee, and Brian Mulloy, VP of Products, captures the knowledge of all these areas gained by Apigee, the leading company in supporting the rollout of high traffic APIs.

    It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

    Today, Intel and other semiconductor firms are abandoning the single fast processor model in favor of multi-core microprocessors--chips that combine two or more processors in a single package. In the fourth edition of "Computer Architecture," the authors focus on this historic shift, increasing their coverage of multiprocessors and exploring the most effective ways of achieving parallelism as the key to unlocking the power of multiple processor architectures. Additionally, the new edition has expanded and updated coverage of design topics beyond processor performance, including power, reliability, availability, and dependability. CD System Requirements"PDF Viewer"The CD material includes PDF documents that you can read with a PDF viewer such as Adobe, Acrobat or Adobe Reader. Recent versions of Adobe Reader for some platforms are included on the CD. "HTML Browser"The navigation framework on this CD is delivered in HTML and JavaScript. It is recommended that you install the latest version of your favorite HTML browser to view this CD. The content has been verified under Windows XP with the following browsers: Internet Explorer 6.0, Firefox 1.5; under Mac OS X (Panther) with the following browsers: Internet Explorer 5.2, Firefox 1.0.6, Safari 1.3; and under Mandriva Linux 2006 with the following browsers: Firefox 1.0.6, Konqueror 3.4.2, Mozilla 1.7.11. The content is designed to be viewed in a browser window that is at least 720 pixels wide. You may find the content does not display well if your display is not set to at least 1024x768 pixel resolution. "Operating System"This CD can be used under any operating system that includes an HTML browser and a PDF viewer. This includes Windows, Mac OS, and most Linux and Unix systems. Increased coverage on achieving parallelism with multiprocessors. Case studies of latest technology from industry including the Sun Niagara Multiprocessor, AMD Opteron, and Pentium 4. Three review appendices, included in the printed volume, review the basic and intermediate principles the main text relies upon. Eight reference appendices, collected on the CD, cover a range of topics including specific architectures, embedded systems, application specific processors--some guest authored by subject experts.

    Fundamentals of Data Structures in C++ offers a complete rendering of basic data structure implementations, enhanced by superior pedagogy and astute analyses.

    Information is provided on the fundamental concepts of table and graph design, the numbers and knowledge most suitable for display in a graphic form, the best tabular means to communicate certain ideas, and the component-level aspects of design. Analysts, technicians, and managers will appreciate the solid theory behind this outline for ensuring that tables and graphs present quantitative business information in a truthful, attractive format that facilitates better decision making.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    Each layer in their application is decoupled from other layers so they can scale, update, and maintain them independently.Kubernetes in Action teaches developers how to use Kubernetes to deploy self-healing scalable distributed applications. By the end, readers will be able to build and deploy applications in a proper way to take full advantage of the Kubernetes platform.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.