No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    Conventional wisdom says most startups need to be in Silicon Valley, started by young engineers around a sexy new idea, and backed by VC funding. But as Mikkel Svane reveals in Startupland, the story of founding Zendesk was anything but conventional.Founded in a Copenhagen loft by three thirty-something friends looking to break free from corporate doldrums, Zendesk Inc. is now one of the hottest enterprise software companies, still rapidly growing with customers in 150 countries. But its success was anything but predestined. With revealing stories both funny and frank, Mikkel shares how he and his friends bravely left secure jobs to start something on their own, how he almost went broke several times, how they picked up themselves and their families to travel across the world to California and the unknown, and how the three friends were miraculously still together for Zendesk's IPO and (still growing) success.Much like Zendesk's mission itself--to remove friction, barriers, and mystery in order to make customer service easier and more approachable--Startupland removes some of the myths about startups and startup founders. Mikkel's advice, hard-won through experience, often bucks conventional wisdom and entrepreneurial tropes. He shares why failure (whether fast or slow) is awful, why a seemingly boring product or idea can be the most exciting, why giving back to the community is as important as the bottom line. From how to hire right (look for people who are not offended by swearing) to which personas generate the highest response rates, Mikkel answers the most pressing questions from the perspective of someone still in the trenches and willing to share the hard truth, warts and all.While there are books by consultants who tell you how to build businesses, or by entrepreneurs now running billion-dollar businesses, there are few books from people still in the trenches who acutely remember the difficult daily decisions, the thrill (and fears) of the early days, the problems that scale with growing a business, and the reason why they all went on the adventure in the first place. Startupland is indispensable reading for all entrepreneurs who want to make their ideas the next big thing. The book will inspire and empower you to follow your own dream and create your own story.

    Presentation Zen challenges the conventional wisdom of making "slide presentations" in today’s world and encourages you to think differently and more creatively about the preparation, design, and delivery of your presentations. Garr shares lessons and perspectives that draw upon practical advice from the fields of communication and business. Combining solid principles of design with the tenets of Zen simplicity, this book will help you along the path to simpler, more effective presentations.--back cover

    How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm Learn how to deploy interactive, batch, and streaming applications Connect to data sources including HDFS, Hive, JSON, and S3 Master advanced topics like data partitioning and shared variables

    It's not just a technical book or just a businessguide. Data is ubiquitous and it doesn't pay much attention toborders, so we've calibrated our coverage to follow it wherever itgoes.In the first edition of Big Data Now, the O'Reilly team tracked thebirth and early development of data tools and data science. Now, withthis second edition, we're seeing what happens when big data grows up:how it's being applied, where it's playing a role, and theconsequences -- good and bad alike -- of data's ascendance.We've organized the second edition of Big Data Now into five areas:Getting Up to Speed With Big Data -- Essential information on thestructures and definitions of big data.Big Data Tools, Techniques, and Strategies -- Expert guidance forturning big data theories into big data products.The Application of Big Data -- Examples of big data in action,including a look at the downside of data.What to Watch for in Big Data -- Thoughts on how big data will evolveand the role it will play across industries and domains.Big Data and Health Care -- A special section exploring thepossibilities that arise when data and health care come together.

    Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes

    R is packed with powerful programming capabilities, but learning to use R in the real world can be overwhelming for even the most seasoned statisticians. This easy-to-follow guide explains how to use R for data processing and statistical analysis, and then, shows you how to present your data using compelling and informative graphics. You'll gain practical experience using R in a variety of settings and delve deeper into R's feature-rich toolset.Includes tips for the initial installation of RDemonstrates how to easily perform calculations on vectors, arrays, and lists of dataShows how to effectively visualize data using R's powerful graphics packagesGives pointers on how to find, install, and use add-on packages created by the R communityProvides tips on getting additional help from R mailing lists and websitesWhether you're just starting out with statistical analysis or are a procedural programming pro, "R For Dummies" is the book you need to get the most out of R.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Adopting Lean will take time and commitment, but it’s vital for harnessing the cultural and technical forces that are accelerating the rate of innovation.* Discover how Lean focuses on people and teamwork at every level, in contrast to traditional management practices* Approach problem-solving experimentally, by exploring solutions, testing assumptions, and getting feedback from real users* Lead and manage large-scale programs in a way that empowers employees, increases the speed and quality of delivery, and lowers costs* Learn how to implement ideas from the DevOps and Lean Startup movements even in complex, regulated environments

    By “reverse engineering the fastest growing company in the history of the world,” author Jeff Jarvis, proprietor of Buzzmachine.com, one of the Web’s most widely respected media blogs, offers indispensible strategies for solving the toughest new problems facing businesses today. With a new afterword from the author, What Would Google Do? is the business book that every leader or potential leader in every industry must read.

    Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught?   In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters."   In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.

    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.

    As they helped grow Google from a young start-up to a global icon, they relearned everything they knew about management. How Google Works is the sum of those experiences distilled into a fun, easy-to-read primer on corporate culture, strategy, talent, decision-making, communication, innovation, and dealing with disruption.The authors explain how the confluence of three seismic changes - the internet, mobile, and cloud computing - has shifted the balance of power from companies to consumers. The companies that will thrive in this ever-changing landscape will be the ones that create superior products and attract a new breed of multifaceted employees whom the authors dub 'smart creatives'. The management maxims ('Consensus requires dissension', 'Exile knaves but fight for divas', 'Think 10X, not 10%') are illustrated with previously unreported anecdotes from Google's corporate history.'Back in 2010, Eric and I created an internal class for Google managers,' says Rosenberg. 'The class slides all read 'Google confidential' until an employee suggested we uphold the spirit of openness and share them with the world. This book codifies the recipe for our secret sauce: how Google innovates and how it empowers employees to succeed.'

    Christensen). We've combed through hundreds of Harvard Business Review articles to select the most important ones to help you maximize yourself.HBR's 10 Must Reads on Managing Yourself will inspire you to:Stay engaged throughout your 50+-year work lifeTap into your deepest valuesSolicit candid feedbackReplenish physical and mental energyBalance work, home, community, and selfSpread positive energy throughout your organizationRebound from tough timesDecrease distractibility and frenzyDelegate and develop employees' initiativeThis collection of best-selling articles includes: bonus article “How Will You Measure Your Life?” by Clayton M. Christensen, "Managing Oneself," "Management Time: Who's Got the Monkey?" "How Resilience Works," "Manage Your Energy, Not Your Time," "Overloaded Circuits: Why Smart People Underperform," "Be a Better Leader, Have a Richer Life," "Reclaim Your Job," "Moments of Greatness: Entering the Fundamental State of Leadership," "What to Ask the Person in the Mirror," and "Primal Leadership: The Hidden Driver of Great Performance."