Dimension Reduction and Latent Factor Models
31 Latent Factors and Matrix Factorization

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

Dimension Reduction and Latent Factor Models
31 Latent Factors and Matrix Factorization

31 Latent Factors and Matrix Factorization

Matrices as data vs matrices in linear algebra - stacked/multimodal vs multiway data SVD, PCA, etc ID and CUR NMF and parts decompositions

Dimension Reduction and Latent Factor Models

32 From Matrices to Tensors