Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. This textbook presents a practical approach to predictive analytics for classroom learning. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. “In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast. 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Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst shows tech-savvy business managers and data analysts how to use predictive analytics to solve practical business problems. Predictive Analytics: Microsoft Excel Predictive Analytics: MicrosoftA Excel Excel predictive analytics for serious data crunchers! Focuses on how to use predictive analytic techniques to analyze historical data for the purpose of predicting future results; Takes an applied approach and focus on solving business problems using predictive analytics and features case studies and a variety of examples; Uses examples in SAS Enterprise Miner, one of world’s leading analytics software tools. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable Python 3 packages. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Updated: July 10, 2019. Timothy has been named a top global business journalist by Richtopia. Readers are shown how to use the results to enable them to develop effective evidence-based HR strategies.”, “Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The authors apply a unified “white box” approach to data mining methods and models. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.”, “Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. As you advance, you’ll get to grips with tasks such as data preparation, exploring and visualizing relationships, building models, and more. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage.”, “Kattamuri Sarma’s Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third Edition, will show you how to develop and test predictive models quickly using SAS Enterprise Miner. Predictive analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future. —David Leinweber, author, Nerds on Wall Street: Math, Machines and Wired Markets The book is accessible, offering nontechnical explanations of the ideas underpinning each approach before introducing mathematical models and algorithms. Carlberg offers unprecedented insight into building powerful, credible, and reliable forecasts, showing how to gain deep insights from Excel that would be difficult to uncover with costly tools such as SAS or SPSS. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. He is a recognized thought leader and influencer in enterprise BI and data analytics. You’ll learn effectively by defining the problem and then moving on to identifying relevant data. In no time, you’ll learn how to incorporate algorithms through data models, identify similarities and relationships in your data, and predict the future through data classification. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets.”, “Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open-source RapidMiner tool. Note: Titles with recently published new editions will be included if the previous edition met our review and ranking criteria. Sorry, your blog cannot share posts by email. A The movie Moneyball made predictive analytics famous: Now you can apply the same techniques to help your business win. The editors at Solutions Review have done much of the work for you, curating this directory of the best predictive analytics books on Amazon. Using realistic data, the book explains complex methods in a simple and practical way to readers from different backgrounds and industries. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning.