Learn everything from basic principles of predictive analytics to using complex predictive models effectively. Discover 9 books that cover it all!

1. 9BOOKSTHAT
MAKE
PREDICTIVE
ANALYTICS
EASY

2. Since Big Data has made some very deep footprints in this era of technology, predictive analysis has
emerged as a highly effective, efficient and lucrative part of data analysis.
Data scientists conduct predictive analyses by:
 Discovering patterns in past and present data through statistics, data mining and machine learning tools
 Creation of models
 Using models to predict business outcomes
THE MAGIC OF
PREDICTIVE ANALYTICS
Businesses act on these predictions, helping them to:
 Retain customers
 Get ahead of trends
 Make informed budget decisions
Want to learn about this magical science?
Introduce yourself to these 9 books, which make it easy!
Brought to you by AIMS InstitutesSource: https://bbfzone-ckatoday.netdna-ssl.com/wp-content/uploads/2015/12/predictiveanalytics-crystal-
ball.jpg

3. #1 PREDICTIVE ANALYTICS
FOR DUMMIES
Authors: Anasse Bari, Mohamed
Chaouchi andTommy Jung
A must read, this 2013 for Dummies
book is the perfect introduction to
predictive analytics (PA).
Less scientific theory and more
practical, you will learn:
 Setting realistic goals
 Creating a PA roadmap
 Real world applications
 Building models
 Employing effective algorithms
Brought to you by AIMS InstitutesSource: http://as.wiley.com/WileyCDA/WileyTitle/productCd-1118728963.html

4. #2PREDICTIVE ANALYTICS
Author: Eric Siegel
Written by a former professor, 2013’s
Predictive Analytics:The Power to
PredictWhoWill Click, Buy, Lie, or Die is
an award winning, industry staple.
Packed with case studies, the book
explores:
 State of the art techniques
 Real world applications
 Privacy and civil liberty concerns
 A wide range of affected industries
Easy to understand, fundamental and
eye opening, this book is a must read for
any aspiring data scientist.
Brought to you by AIMS InstitutesSource: https://www.salford-systems.com/news/salford-systems-cart-featured-in-new-predictive-
analytics-book

5. #3APPLIED PREDICTIVE MODELING
Authors: Max Kuhn and Kjell Johnson
An experienced statistician’s guide to problem solving
with real data, this 2013 publication provides tools for
data analysts to create predictive models for yet-to-be-
seen data.
An in depth study for both beginners and experienced
model builders, the book covers:
 Case studies
 Using R to create graphs
 Making accurate predictions
 Classification and regression models
Brought to you by AIMS InstitutesSource: http://www.texata.com/resources/books/

6. #4APPLIED PREDICTIVE ANALYTICS
Author: Dean Abbott
Applied Predictive Analytics: Principles
andTechniques for the Professional Data
Analyst is a 2014 publication.
Armed with hands on examples and case
studies, the book explains:
Theory behind predictive analytics
 Principles and techniques for PA
projects
 How to successfully apply principles
to achieve solutions
Readers can apply their knowledge
using the companion website and free
software trial that comes with the book.
Brought to you by AIMS InstitutesSource: https://www.bookdepository.com/Applied-Predictive-Analytics-Dean-Abbott/
9781118727966

7. #5THE SIGNAL AND THE NOISE
Author: Nate Silver
Originally published in 2012, The Signal
and the Noise:Why So Many Prediction Fail
– and Some Don’t is written by an expert
political forecaster.
Interspersed with personal stories and
musings, the book explores what sets
good predictions apart from bad ones.
The discussion considers:
 Using biased data sets
 Using elaborate models to wrongly fit
data
 Ascertaining an underlying theory to
guide predictions
 Bayesian methods of prediction
Brought to you by AIMS InstitutesSource: http://www.bookdepository.com/The-Signal-and-the-Noise-Nate-
Silver/9780143125082?ref=grid-view

8. #6THE ELEMENTS
OF STATISTICAL LEARNING
Authors:Trevor Hastie, Robert
Tibshirani and Jerome Friedman
Published in 2001, this classic and
comprehensive book covers:
 Supervised and unsupervised learning
 Neural networks
 Support vector machines
 Classification trees
The first book to address data mining,
inference and prediction from an all
inclusive approach, it remains relevant
to statisticians and data analysts even
today.
Brought to you by AIMS InstitutesSource: http://www.bookdepository.com/The-Elements-of-Statistical-Learning-Trevor-Hastie-
Robert-Tibshirani-Jerome-Friedman/9781489905185?ref=grid-view

9. #7DATA MINING
Authors: Ian H. Witten, Eibe Frank and Mark
A. Hall
Data Mining: Practical Machine Learning
Tools andTechniques was originally
published in 1999.
Updated since then, readers can explore:
 Machine learning concepts
 Applying predictive tools in real world
data mining situations
 Ensemble learning
 Performance improvement tips and tricks
Weka’s machine learning software toolkit
comes with the latest edition, allowing
readers to practice and implement the data
mining methods in the book.
Brought to you by AIMS InstitutesSource: http://www.bookdepository.com/Dat-Mining-Ian-H-Witten-Eibe-Frank-Mark--Hall-
Geoffrey-Holmes/9780123748560?ref=grid-view

10. #8UNCONTROLLED
Author: Jim Manzi
Published in 2012, Uncontrolled:The
Surprising Payoff ofTrial-and-Error for
Business, Politics, and Society explores:
The scientific method and why controlled
experimentation assures accurate predictions
in business.
The unrealised potential of Randomized
FieldTrials and examples of how they can
change businesses.
The books claims that controlled
experimentation reduces the risk of
inaccurate predictive models and can even
augment the results of predictive analytics.
Brought to you by AIMS InstitutesSource: http://www.bookdepository.com/Uncontrolled-Jim-Manzi/9780465023240?ref=grid-view

11. #9MODELING TECHNIQUES IN
PREDICTIVE ANALYTICS
Author:Thomas W. Miller
In this 2014 guide to data science,
Professor Miller explains:
 Using languages R and Python to
solve real business problems
 Maximizing the value of different
models
 Crafting and optimizing models
The book is a step by step, highly
useful guide to determining
problems, pulling data and reaching
applicable business results.
WITH PYTHON & R
Brought to you by AIMS InstitutesSource: http://www.bookdepository.com/Modeling-Techniques-in-Predictive-Analytics-with-
Python-and-R-Thomas-W-Miller/9780133892062?ref=grid-view

12. ANALYZE YOUR FUTURE!
As predictive analytics reaches industries from finance to law enforcement,
there’s every chance you will come across it.
Study the impressive science of predictive analytics by considering an
industry relevant business analytics course by IBM at AIMS Institutes.
Brought to you by AIMS InstitutesSource: http://predictiveanalytics.org