Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science
ISBN: 0133892069
EAN13: 9780133892062
Language: English
Pages: 418
Dimensions: 1.00" H x 9.00" L x 7.00" W
Weight: 2.00 lbs.
Format: Hardcover
Book Overview
Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R not complex math. Step by step, you ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today s key applications for predictive analytics, delivering skills and knowledge to put models to work and maximize their value. Thomas W. Miller, leader of Northwestern University s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you re new to predictive analytics, you ll gain a strong foundation for achieving accurate, actionable results. If you re already working in the field, you ll master powerful new skills. If you re familiar with either Python or R, you ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http: //www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you re already a modeler, programmer, or manager, you ll learn crucial skills you don t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You ll learn why each problem matters, what data are relevant, and how to explore the data you ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more