Applied Predictive Analytics (Paperback)

Dean Abbott

ISBN 10: 1118727967 / ISBN 13: 9781118727966

Published by John Wiley & Sons Inc, New York, 2014

About this Item

Paperback. 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 todayThis guide teaches not only the principles of predictive analytics, but also how to apply them to achieve real, pragmatic solutionsExplains methods, principles, and techniques for conducting predictive analytics projects from start to finishIllustrates each technique with hands-on examples and includes as series of in-depth case studies that apply predictive analytics to common business scenariosA 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. Written by one of the leading experts on predictive analytics, Applied Predictive Analytics shows tech-savvy business managers and data analysts how to use the sophisticated techniques of predictive analytics that mine Big Data to solve practical business problems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9781118727966

Bibliographic Details

• Title: Applied Predictive Analytics (Paperback)
• Publisher: John Wiley & Sons Inc, New York
• Publication Date: 2014
• Language: English
• ISBN 10: 1118727967
• ISBN 13: 9781118727966
• Binding: Paperback
• Edition: 1st Edition
• Condition: new

About this title

Synopsis

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.

About the Author

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 SmarterRemarketer, a company focusing on behaviorally- and data-driven marketing and web analytics.