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

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: