Book Content
chapters • 19h12m total length
1. Getting Started with Predictive Analytics
2. The Modeling process
3. Inputting and Exploring Data
4. Introduction to Basic Algorithms
5. Introduction to Decision trees, Clustering, and SVM
6. Using Survival Analysis to Predict and Analyze Customer Churn
7. Using Market Basket Analysis as a Recommender Engine
8. Exploring Health Care Enrollment Data as a Time Series
9. Introduction to Spark Using R
10. Exploring Large Datasets Using Spark
11. Spark Machine Learning – Regression and Cluster Models
12. Spark Models – Rule-Based Learning
