This book provides an essential guide for data science and machine learning practitioners looking to deepen their understanding of abstract mathematical concepts and bridge the gap between coding and theoretical research. By combining mathematical rigor with practical, programmable examples, it transforms complex ideas--such as groups, manifolds, and quotient spaces--into accessible computational frameworks. Perfect for emerging data scientists and engineers, this book empowers readers to move beyond simply using AI tools and equips them with the knowledge to fundamentally understand the principles that shape them.
Related Subjects
Computers Computers & Technology Engineering Math Mathematics Science & Math Technology