Mastering Machine Learning with R

Table of Contents

1. Preparing and Understanding Data
2. Linear Regression
3. Logistic Regression
4. Advanced Feature Selection in Linear Models
5. K-Nearest Neighbors and Support Vector Machines
6. Tree-Based Classification
7. Neural Networks and Deep Learning
8. Creating Ensembles and Multiclass Methods
9. Cluster Analysis
10. Principal Component Analysis
11. Association Analysis
12. Time Series and Causality
13. Text Mining
14. Appendix A- Creating a Package