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This paperback volume covers linear algebra and optimization with applications to machine learning, focusing on concepts relevant to computer vision, robotics, and related ML problems. It is the first volume in a series and comprises 824 pages of structured mathematical content, offering a detailed treatment of foundational topics and their practical use in modern computational contexts. The work presents theoretical developments alongside algorithmic considerations, making it a substantial reference for graduate-level study and advanced coursework in machine learning, computer vision, and robotics.
| Edition | Volume I |
| Format | Paperback |
| Pages | 824 |
| Publisher | World Scientific Publishing Company |
| Subject | Linear Algebra, Optimization, Machine Learning |