Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science

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9780133892062: Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science
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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

From the Publisher:

Compete on analytics: win by understanding your data more deeply than your competitors do! In Modeling Techniques in Predictive Analytics, the Python edition, the leader of Northwestern University's prestigious analytics program brings together all the up-to-date concepts, techniques, and Python code you need to excel in analytics. Thomas W. Miller's balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. This important reference addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, Web and text analytics, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains: * Why the problem is significant * What data is relevant * How to explore your data * How to model your data - first conceptually, with words and figures; and then with mathematics and programs Miller walks through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. Extensive example code is presented in Python, a new and extremely popular language for applied statistics, statistical research, and predictive modeling; all code is set apart from other text so it's easy to find if you want it (and easy to skip if you don't).

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Descripción Pearson Education (US), United States, 2014. Hardback. Estado de conservación: New. 1st Revised edition. 239 x 183 mm. Language: English . Brand New Book. 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 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. Nº de ref. de la librería AAS9780133892062

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Descripción Pearson Education (US), United States, 2014. Hardback. Estado de conservación: New. 1st Revised edition. 239 x 183 mm. Language: English . Brand New Book. 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 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. Nº de ref. de la librería AAS9780133892062

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Descripción Hardcover. Estado de conservación: New. 1st Revised edition. 187mm x 239mm x. Hardcover. 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 T.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 448 pages. 0.914. Nº de ref. de la librería 9780133892062

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