Whether it's improving customer experiences, trying out new business models, or developing new products, even the most experienced managers often get it wrong. This is especially true in the online world, where predicting customer behavior is virtually impossible.Managers can, however, discover whether a new product, service, or business model will fail or succeed--by subjecting it to rigorous experimentation. Think about it. A pharmaceutical company would never introduce a new drug without first conducting a round of experiments based on established scientific protocols. Yet that's essentially what many companies do when they roll out new products and services.As Harvard Business School professor Stefan Thomke shows in this eye-opening and essential book, the "best guess" approach to innovation is changing fast. There are now leading companies that conduct more than ten thousand online controlled experiments annually, engaging millions of users. These organizations have discovered that an "experiment with everything" approach has a big payoff, giving them a considerable competitive advantage.How can you do this at your company? Leaders and managers need to create an "experimentation organization" that masters the science of testing and puts the discipline of experimentation at the center of the innovation process. It used to take companies years to build the infrastructure and develop the expertise to run hundreds of experiments each day. But Thomke shows how, with advances in technology, these capabilities are at the fingertips of almost any business professional. By combining the power of software and the rigor of controlled experiments, today's managers can make better decisions, create better customer experiences, and generate huge financial returns.Filled with engaging and instructive stories of leading experimentation organizations, Experimentation Works will be your guidebook to a truly new way of thinking and innovating.

    This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champion Go player, achieving superhuman performance on video games, driving cars, translating languages, and sometimes even helping law enforcement fight crime. Deep Learning is a revolution that is changing every industry across the globe.Grokking Deep Learning is the perfect place to begin your deep learning journey. Rather than just learn the “black box” API of some library or framework, you will actually understand how to build these algorithms completely from scratch. You will understand how Deep Learning is able to learn at levels greater than humans. You will be able to understand the “brain” behind state-of-the-art Artificial Intelligence. Furthermore, unlike other courses that assume advanced knowledge of Calculus and leverage complex mathematical notation, if you’re a Python hacker who passed high-school algebra, you’re ready to go. And at the end, you’ll even build an A.I. that will learn to defeat you in a classic Atari game.

    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

    This is no ordinary "how-to" manual for CFA candidates. Written by an internationally published author who passed all three CFA exams on the first try, this book is packed with real strategies that get real results. What tactics make the difference? How do passing candidates set themselves apart? Direct Path to the CFA Charter enables you to adopt the right methods and strategies to pass the exams the first time around. With actionable takeaways, sample study schedules, and unique tips for every CFA Level, this book is for the serious candidate who not only wants to understand the CFA Program, but succeed in it.

    

    It is a direct result of bad choices made overtime that eventually turned into habits that masters you. Like a thermostat, once these habits are set, it becomes nearly impossible to break them without deliberate and intentional effort. 21 Habits of Highly Broke People dives into details on the habits that keeps people poor, and practical action steps you can take to break free from these habits. 21 Habits of Highly Broke People shows you: 1. How your choices about money is keeping you broke. 2. What the rich do differently from the poor. 3. How to break bad habits and replace them with positive habits.

    In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect.Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor.In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile.The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values.This deeply researched and passionate book could not be more timely.Naomi Klein: "This book is downright scary."Ethan Zuckerman, MIT: "Should be required reading."Dorothy Roberts, author of Killing the Black Body: "A must-read for everyone concerned about modern tools of inequality in America."Astra Taylor, author of The People's Platform: "This is the single most important book about technology you will read this year."

    Author David Parmenter provides you with everything you need to master and implement a KPI-driven strategy.

    

    This connectedness is found in many incarnations: in the rapid growth of the Internet, in the ease with which global communication takes place, and in the ability of news and information as well as epidemics and financial crises to spread with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which our decisions can have subtle consequences for others. This introductory undergraduate textbook takes an interdisciplinary look at economics, sociology, computing and information science, and applied mathematics to understand networks and behavior. It describes the emerging field of study that is growing at the interface of these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

    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.

    straight from an experienced pro that has seen millions of dollars exchange hands at the closing table.” - Peter Voogd, #1 International Bestselling Author of 6 Months to 6 Figures There are countless real estate books on the market today, so why read this one? What sets it apart from all the others out there?Bestselling Author, Alex Goldstein, brings a unique perspective that many others do not. As a successful realtor and investor, Alex has been on both sides of a real estate transaction, so he knows what strategies and techniques will lead to a successful deal, and which ones should be avoided at all costs. That’s why he chose the name, "No Nonsense Real Estate," for his third book.Goldstein offers practical, proven home buying techniques, free of fluff or confusing jargon.This book is for anyone who is getting ready to buy or sell a home and wants to be as informed as possible as they get ready to begin the process so there are no surprises – whether they will be working with a realtor or doing it on their own. 9 REASONS TO READ THIS BOOK NOW: 1. AGENT - Go through the pros and cons of working with a real estate agent, and the two ways that they can add the most value,2. ECONOMICS - You'll understand the fundamental economics of the housing market in the simplest terms possible3. INVESTING - Avoid the top five mistakes (almost) all new real estate investors make4. NEGOTIATIONS - Five critical elements of a successful negotiation5. FINANCING - Possible financing options, from traditional loans to seller financing6. SELLING - Seven secrets that make selling a home as painless as possible7. BUYING - Demystifying contracts and closing costs takes the fear out of the process8. CLOSING - Walk through eight steps involved in a real estate transaction closing9. PRACTICAL - Learn how all the different parts come together in a real life case studyYou also receive three free gifts. Goldstein has put together a special document answering the most popular questions every buyer, seller or investor has during a real estate transaction. You also get special access to an easy-to-understand glossary of the most popular real estate jargon. Last but not least, every reader is access to a free video training that will teach you how to choose the best home for your family.

    

    Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.