Dean Abbott 
Applied Predictive Analytics 
Principles and Techniques for the Professional Data Analyst

Learn the art and science of predictive analytics —
techniques that get results

Predictive analytics is what translates big data into
meaningful, usable business information. Written by a leading
expert in the field, this guide examines the science of the
underlying algorithms as well as the principles and best practices
that govern the art of predictive analytics. It clearly explains
the theory behind predictive analytics, teaches the methods,
principles, and techniques for conducting predictive analytics
projects, and offers tips and tricks that are essential for
successful predictive modeling. Hands-on examples and case studies
are included.

* The ability to successfully apply predictive analytics enables
businesses to effectively interpret big data; essential for
competition today

* This guide teaches not only the principles of predictive
analytics, but also how to apply them to achieve real, pragmatic
solutions

* Explains methods, principles, and techniques for conducting
predictive analytics projects from start to finish

* Illustrates each technique with hands-on examples and includes
as series of in-depth case studies that apply predictive analytics
to common business scenarios

* A companion website provides all the data sets used to generate
the examples as well as a free trial version of software

Applied Predictive Analytics arms data and business
analysts and business managers with the tools they need to
interpret and capitalize on big data.

A propos de l’auteur

DEAN ABBOTT is President of Abbott Analytics, Inc. (San
Diego). He is an internationally recognized data mining and
predictive analytics expert with over two decades experience in
fraud detection, risk modeling, text mining, personality
assessment, planned giving, toxicology, and other applications. He
is also Chief Scientist of Smarter Remarketer, a company focusing on
behaviorally- and data-driven marketing and web analytics.