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

Applied Predictive Analytics - Principles and Techniques for the Professional Data Analyst

Szerző: Dean Abbott
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten alacsony példányszámban
Küldés 11-15 napon belül
18 155 Ft
Learn the art and science of predictive analytics -- techniques that get results§Predictive analytic...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2014
oldal
464
EAN
9781118727966
ISBN
1118727967
Enbook ID
02311106
Súly
820
Méretek
189 x 236 x 21

Teljes leírás

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.

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