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.

    It’s easy and fun with this practical, hands-on introduction. Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser. Along the way, you’ll expand your web programming skills, using tools such as HTML and JavaScript.This step-by-step guide is ideal whether you’re a designer or visual artist with no programming experience, a reporter exploring the new frontier of data journalism, or anyone who wants to visualize and share data.Learn HTML, CSS, JavaScript, and SVG basicsDynamically generate web page elements from your data—and choose visual encoding rules to style themCreate bar charts, scatter plots, pie charts, stacked bar charts, and force-directed layoutsUse smooth, animated transitions to show changes in your dataIntroduce interactivity to help users explore data through different viewsCreate customized geographic maps with dataExplore hands-on with downloadable code and over 100 examples

    The title says it is the hard way to learn to writecode but it’s actually not. It’s the “hard” way only in that it’s the way people used to teach things. In this book youwill do something incredibly simple that all programmers actually do to learn a language: 1. Go through each exercise. 2. Type in each sample exactly. 3. Make it run.That’s it. This will be very difficult at first, but stick with it. If you go through this book, and do each exercise for1-2 hours a night, then you’ll have a good foundation for moving on to another book. You might not really learn“programming” from this book, but you will learn the foundation skills you need to start learning the language.This book’s job is to teach you the three most basic essential skills that a beginning programmer needs to know:Reading And Writing, Attention To Detail, Spotting Differences.

    QRI-5

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    

    A real life case study with sample project documents and diagrams is used to more practically explain these international tools, techniques, and lean principles to a broad range of practitioners, including: - Business analysts, systems analysts, developers and project managers - Entrepreneurs, product owners and product managers - Consultants, UX designers and marketing specialists - C-suite executives, investors and managers of companies of all sizes.

    By using the Framework you will learn architectural best practices for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud.

    Now, Core JavaServer™ Faces–the #1 guide to JSF–has been thoroughly updated in this second edition, covering the latest feature enhancements, the powerful Ajax development techniques, and open source innovations that make JSF even more valuable. Authors David Geary and Cay Horstmann delve into all facets of JSF 1.2 development, offering systematic best practices for building robust applications, minimizing handcoding, and maximizing productivity. Drawing on unsurpassed insider knowledge of the Java platform, they present solutions, hints, tips, and “how-tos” for writing superior JSF 1.2 production code, even if you’re new to JSF, JavaServer Pages™, or servlets.The second edition’s extensive new coverage includes: JSF 1.2’s improved alignment with the broader Java EE 5 platform; enhancements to the JSF APIs; controlling Web flow with Shale; and using Facelets to replace JSP with XHTML markup. The authors also introduce Ajax development with JSF–from real-time validation and Direct Web Remoting to wrapping Ajax in JSF components and using the popular Ajax4jsf framework.This book will help you Automate low-level details and eliminate unnecessary complexity in server-side development Discover JSF best practices, ranging from effective UI design and style sheets to internationalization Use JSF with Tiles to build consistent, reusable user interfaces Leverage external services such as databases, LDAP directories, authentication/authorization, and Webservices Use JBoss Seam to greatly simplify development of database-backed applications Implement custom components, converters, and validators Master the JSF 1.2 tag libararies, and extend JSF with additional tag libraries Preface Acknowledgments Chapter 1: Getting Started Chapter 2: Managed Beans Chapter 3: Navigation Chapter 4: Standard JSF Tags Chapter 5: Data Tables Chapter 6: Conversion and Validation Chapter 7: Event Handling Chapter 8: Subviews and Tiles Chapter 9: Custom Components, Converters, and Validators Chapter 10: External Services Chapter 11: Ajax Chapter 12: Open Source Chapter 13: How Do I . . . Index

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    Keeping themorganized can be a challenge, but an organized classroom is essential and allows students and the teacher to fully focus on learning by eliminating distractions. Organized Teacher, Happy Classroom provides practical, proven methods for maintaining an organized classroom throughout the entire school year.Inside you’ll find:• Strategies for managing students’ papers, curriculum material, and essential paperwork• Time management tips to maximize your instruction time and lesson planning• Organizing systems you can teach your students to improve self reliance andaccountability• Checklists for starting and ending the year well organized• Helpful forms and templates you can use in your classroom• Plans for arranging a classroom that promotes positive student participation• Support to simplify your classroom• Efficient storage solutions for all teacher and student materialsWhether you teach primary, intermediate, middle school or high school, this bookwill help you organize your time, paperwork, and classroom spaces.

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    For courses in computer organization and architecture, this text provides a clear, comprehensive presentation of the organization and architecture of contemporary computers.

    The authors help students learn key sociological concepts through real research examples related to the dynamic interplay of race, class, gender, and other social variables.

    With jokes, puns, and a rigorous problem solving based approach. You can download all the code samples used in the book from here: http://www.robmiles.com/s/Yellow-Book...