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- AI & Machine Learning /
- Computer Vision & Pattern Recognition /
- Mathematical Analysis of Machine Learning Alg...
Mathematical Analysis of Machine Learning Algorithms
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XOF 44384
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- The mathematical theory of machine learning not only explains the current algorithms but can also motivate principled approaches for the future. This self-contained textbook introduces students and researchers of AI to the main mathematical techniques used to analyze machine learning algorithms, with motivations and applications. Topics covered include the analysis of supervised learning algorithms in the iid setting, the analysis of neural networks (e.g. neural tangent kernel and mean-field analysis), and the analysis of machine learning algorithms in the sequential decision setting (e.g. online learning, bandit problems, and reinforcement learning). Students will learn the basic mathematical tools used in the theoretical analysis of these machine learning problems and how to apply them to the analysis of various concrete algorithms. This textbook is perfect for readers who have some background knowledge of basic machine learning methods, but want to gain sufficient technical knowledge to understand research papers in theoretical machine learning.
| Publisher | Cambridge University Press |
| Publication date | August 10, 2023 |
| Edition | 1st |
| Language | English |
| Print length | 468 pages |
| ISBN-10 | 1009098381 |
| ISBN-13 | 978-1009098380 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 1.25 x 10 inches (17.8 x 3.2 x 25.4 cm) |
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Mathematical Analysis of Machine Learning Algorithms
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XOF 44384
Yi Oda yanzu, a samu nan da Juma'a, Oktoba 30
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