Practical Predictive Analytics
This book teaches six specific steps needed to implement predictive analytics using R. It also teaches how team collaboration is critical and how it increases the chances of implementing a successful model. The book uses cases from healthcare, marketing, and government to build practical skills. Big Data is also covered, in this book, which will extend your skill sets by learning Databricks and RSpark.
Offered by
Difficulty Level
Intermediate
Completion Time
19h12m
Language
English
About Book
Who Is This Book For?
This book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues. Basic familiarity with a programming language of R is expected.
Practical Predictive Analytics
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 19h12m total length
Getting Started with Predictive Analytics
The Modeling process
Inputting and Exploring Data
Introduction to Basic Algorithms
Introduction to Decision trees, Clustering, and SVM
Using Survival Analysis to Predict and Analyze Customer Churn
Using Market Basket Analysis as a Recommender Engine
Exploring Health Care Enrollment Data as a Time Series
Introduction to Spark Using R
Exploring Large Datasets Using Spark
Spark Machine Learning – Regression and Cluster Models
Spark Models – Rule-Based Learning
Related Resources
Access Ready-to-Use Books for Free!
Get instant access to a library of pre-built books—free trial, no credit card required. Start training your team in minutes!