Fundamentals in 1D
15 Computing with Randomness

Numerical Methods for Data Science

Preface
1 Introduction
Background Plus a Bit
Fundamentals in 1D
Numerical Linear Algebra
Nonlinear Equations and Optimization
Computing with Randomness
Dimension Reduction and Latent Factor Models
Function Approximation
Network Analysis
Learning Dynamics
References

Fundamentals in 1D
15 Computing with Randomness

15 Computing with Randomness

NB: Maybe this is just section 4

Randomized methods - Monte Carlo and Las Vegas Variational inference (??) Probabilistic numerics (including BQ) Uncertainty quantification

14 Root Finding and Optimization

Numerical Linear Algebra