Books
Offers common use cases to help you get started
Covers details on modeling, machine learning, and more
Includes information on structuring your data
Provides tips on outlining business goals and approaches
The future starts today with the help of Predictive Analytics For Dummies.
Books by Prof. Bari
Abstract
You don't need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast. With the help of this friendly guide, you'll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. In no time, you'll learn how to incorporate algorithms through data models, identify similarities and relationships in your data, and predict the future through data classification. Along the way, you'll develop a roadmap by preparing your data, creating goals, processing your data, and building a predictive model that will get you stakeholder buy-in.
Big Data has taken the marketplace by storm, and companies are seeking qualified talent to quickly fill positions to analyze the massive amount of data that are being collected each day. If you want to get in on the action and either learn or deepen your understanding of how to use predictive analytics to find real relationships between what you know and what you want to know, everything you need is a page away!
Reviews
Forbes, 2016:
“5 Mistakes That Can Kill Your Digital Analytics”
“Predictive Analytics is becoming the next big buzzword in the industry, with books like Predictive Analytics For Dummies topping the Amazon charts.”
Bookauthority, 2019:
“39 Best Predictive Modeling Books of All Time” – Ranked #3
(As featured on CNN, Forbes and Inc. BookAuthority identifies and rates the best books in the world, based on public mentions, recommendations, ratings and sentiment.)
Solutions Review, 2015:
“Top 10 Books on Predictive Analytics and Data Modeling”
“Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions...”
Insights Analytics, 2019:
“Predictive Analytics For Dummies – A Review”
“The book dove right in and covered the techniques of predictive analytics that utilize historical data that primarily provide estimates about the outcomes of our enterprises. The first parts covered only the very basic needs of understanding when it comes to predictive analytics for your department or company. Wiley (the publisher) did a nice job with the multiple author selection with Anasse Bari, PhD, Mohamed Chaouchi, and Tommy Jung.”
Table of Contents
For a more detailed table of contents (with more details on each chapter) please click here.
INTRODUCTION 1
PART 1: GETTING STARTED WITH PREDICTIVE ANALYTICS 5
CHAPTER 1: Entering the Arena 7
CHAPTER 2: Predictive Analytics in the Wild 23
CHAPTER 3: Exploring Your Data Types and Associated Techniques 51
CHAPTER 4: Complexities of Data 69
PART 2: INCORPORATING ALGORITHMS IN YOUR MODELS 89
CHAPTER 5: Applying Models 91
CHAPTER 6: Identifying Similarities in Data 115
CHAPTER 7: Predicting the Future Using Data Classification 147
PART 3: DEVELOPING A ROADMAP 185
CHAPTER 8: Convincing Your Management to Adopt Predictive Analytics 187
CHAPTER 9: Preparing Data 209
CHAPTER 10: Building a Predictive Model 229
CHAPTER 11: Visualization of Analytical Results 245
PART 4: PROGRAMMING PREDICTIVE ANALYTICS 265
CHAPTER 12: Creating Basic Prediction Examples 267
CHAPTER 13: Creating Basic Examples of Unsupervised Predictions 299
CHAPTER 14: Predictive Modeling with R 323
CHAPTER 15: Avoiding Analysis Traps 359
PART 5: EXECUTING BIG DATA 381
CHAPTER 16: Targeting Big Data 383
CHAPTER 17: Getting Ready for Enterprise Analytics 399
PART 6: THE PART OF TENS 411
CHAPTER 18: Ten Reasons to Implement
CHAPTER 19: Ten Steps to Build a Predictive Analytic Model 423
INDEX