Simulation for Data Science with R

Table of Contents

1. Introduction
2. R and high-performance computing
3. The discrepancy between Pencil driven theory and Data driven computational solutions
4. Simulation of random numbers
5. Monte-Carlo methods for optimization problems
6. Probability theory shown by simulation
7. Resampling Methods
8. Applications of resampling methods and Monte Carlo tests
9. The EM algorithm
10. Simulation of complex data
11. System dynamics