Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective codeain 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. Youall master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and Ranot complex math. Step by step, youall 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 todayas key applications for predictive analytics, delivering skills and knowledge to put models to workaand maximize their value. Thomas W. Miller, leader of Northwestern Universityas pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If youare new to predictive analytics, youall gain a strong foundation for achieving accurate, actionable results. If youare already working in the field, youall master powerful new skills. If youare familiar with either Python or R, youall 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. Milleras 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 youare new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If youare already a modeler, programmer, or manager, youall learn crucial skills you donat 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. Youall learn why each problem matters, what data are relevant, and how to explore the data youave 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. Youall 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 moreA Guide to Data Science Thomas W. Miller. Sometimes referred to as a aglue language, a Python provides a rich opensource environment for scientific ... We help researchers and analysts by providing a ready resource and reference guideanbsp;...
|Title||:||Modeling Techniques in Predictive Analytics with Python and R|
|Author||:||Thomas W. Miller|
|Publisher||:||FT Press - 2014-09-29|