EUR 60,39 + Envío GRATIS
Hay una versión más barata de este libro
Ahorra EUR 32,11 (42%) al elegir la edición Kindle.
EUR 28,28
Precio Kindle
EUR 60,39
Precio tapa dura

Ahorra <span class="a-color-price">EUR 32,11 (42%)</span> al elegir la edición Kindle. Lee ahora con la aplicación de lectura Kindle gratuita, disponible para iOS, Android, Mac y PC.
  • Precio recomendado: EUR 75,81
  • Ahorras: EUR 15,42 (20%)
  • Precio final del producto
Sólo queda(n) 2 en stock.
Vendido y enviado por The_Book_Depository_ES.
EUR 60,39 + Envío GRATIS
Compara Precios en Amazon
Añadir a la cesta
EUR 58,49
Envío GRATIS disponible. Ver detalles.
Vendido por: Amazon
¿Tienes uno para vender? Vender en Amazon
Volver atrás Ir adelante
Escuchar Reproduciendo... Interrumpido   Estás escuchando una muestra de la edición de audio Audible.
Más información
Ver las 2 imágenes

Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science (Inglés) Tapa dura – 1 oct 2014


Ver los 7 formatos y ediciones Ocultar otros formatos y ediciones
Precio Amazon
Nuevo desde Usado desde
Versión Kindle
Tapa dura
EUR 60,39
EUR 58,49 EUR 57,98
click to open popover

Descripción del producto

Reseña del editor

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

Biografía del autor

THOMAS W. MILLER is faculty director of the Predictive Analytics program at Northwestern University. He has designed courses for the program, including Marketing Analytics, Advanced Modeling Techniques, Data Visualization, Web and Network Data Science, and the capstone course. He has taught extensively in the program and works with more than forty other faculty members in delivering training in predictive analytics and data science. Miller is co-founder and director of product development at ToutBay, a publisher and distributor of data science applications. He has consulted widely in the areas of retail site selection, product positioning, segmentation, and pricing in competitive markets, and has worked with predictive models for over 30 years. Miller's books include Data and Text Mining: A Business Applications Approach, Research and Information Services: An Integrated Approach for Business, and a book about predictive modeling in sports, Without a Tout: How to Pick a Winning Team. Before entering academia, Miller spent nearly 15 years in business IT in the computer and transportation industries. He also directed the A. C. Nielsen Center for Marketing Research and taught market research and business strategy at the University of Wisconsin-Madison. He holds a Ph.D. in psychology (psychometrics) and a master's degree in statistics from the University of Minnesota, and an MBA and master's degree in economics from the University of Oregon.

No es necesario ningún dispositivo Kindle. Descárgate una de las apps de Kindle gratuitas para comenzar a leer libros Kindle en tu smartphone, tablet u ordenador.

  • Apple
  • Android
  • Windows Phone

Obtén la app gratuita:



Detalles del producto


Opiniones de clientes

No hay opiniones de clientes
Comparte tu opinión con otros clientes

Opiniones de clientes más útiles en Amazon.com

Amazon.com: 3,5 de 5 estrellas 25 opiniones
JoeT
4,0 de 5 estrellasGood book for end-users
27 de diciembre de 2013 - Publicado en Amazon.com
Compra verificada
A 20 personas les ha parecido esto útil.
Prof Ed U. Cate
3,0 de 5 estrellasMore like a collection of magazine/newspaper articles than a book
27 de diciembre de 2013 - Publicado en Amazon.com
Compra verificada
A 58 personas les ha parecido esto útil.
PenName
1,0 de 5 estrellasWaste of money
31 de agosto de 2016 - Publicado en Amazon.com
Compra verificada
A 2 personas les ha parecido esto útil.
Joshua W Smitherman
4,0 de 5 estrellasGreat overview of real examples in business with nice visualizations capabilities shown
23 de enero de 2014 - Publicado en Amazon.com
Compra verificada
A 4 personas les ha parecido esto útil.
Daniel Gonzales
5,0 de 5 estrellasFive Stars
15 de agosto de 2017 - Publicado en Amazon.com
Compra verificada