Mathematics of Data Science
Summary
This arXiv entry presents Mathematics of Data Science, a mathematical foundation text for data science. It covers core topics such as SVD/PCA, linear regression and regularization, graphs and networks, diffusion maps, random projections, optimization, classification, and an introduction to deep learning, along with concentration of measure, matrix inequalities, compressive sensing, and low-rank recovery.