Mathematics of Data Science
3 hours ago
- #Machine Learning
- #Data Science
- #Mathematics
- The book covers the mathematical foundations of data science, including topics like high-dimensional spaces, singular value decomposition, linear regression, graphs and networks, and deep learning.
- It addresses key techniques such as dimensionality reduction (both linear and nonlinear), optimization, classification, compressive sensing, and matrix recovery.
- The text also explores theoretical aspects like concentration of measure, Gaussian analysis, and matrix concentration inequalities, providing a comprehensive introduction to the mathematics behind data science.