Applied Mathematics for Data Science

This book presents fundamental mathematical concepts in a clear, practical, and application-oriented manner. It focuses on areas such as linear algebra, calculus, probability theory, statistics, optimization, and numerical methods—each explained with relevance to modern data science problems. Rather than emphasizing abstract proofs alone, the text highlights how mathematical principles power machine learning models, artificial intelligence systems, and analytical decision-making.