Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science (FT Press Analytics),Used

Master predictive analytics, from start to finishStart with strategy and managementMaster methods and build modelsTransform your models into highlyeffective codein both Python and RThis oneofakind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. Youll master predictive analytics through realistic case studies, intuitive data visualizations, and uptodate code for both Python and Rnot complex math.Step by step, youll 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 todays key applications for predictive analytics, delivering skills and knowledge to put models to workand maximize their value.Thomas W. Miller, leader of Northwestern Universitys pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code.If youre new to predictive analytics, youll gain a strong foundation for achieving accurate, actionable results. If youre already working in the field, youll master powerful new skills. If youre familiar with either Python or R, youll 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. Millers 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 youre new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If youre already a modeler, programmer, or manager, youll learn crucial skills you dont 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 crosssectional data, time series, spatial, and spatiotemporal data.Youll learn why each problem matters, what data are relevant, and how to explore the data youve 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.Youll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving outofsample 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