Mathematics of Data Science — foundational textbook on arXiv
Comprehensive treatment of the mathematical theory underpinning modern data science, from linear algebra through deep learning.
• High-dimensional geometry, SVD, PCA, and linear regression
• Graphs, networks, clustering, and nonlinear dimension reduction
• Optimization, classification, and deep learning theory
• Concentration inequalities, matrix recovery, and compressive sensing