Mathematics for Machine Learning
(Sprache: Englisch)
Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.
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Produktinformationen zu „Mathematics for Machine Learning “
Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.
Klappentext zu „Mathematics for Machine Learning “
This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Inhaltsverzeichnis zu „Mathematics for Machine Learning “
1. Introduction and motivation; 2. Linear algebra; 3. Analytic geometry; 4. Matrix decompositions; 5. Vector calculus; 6. Probability and distribution; 7. Optimization; 8. When models meet data; 9. Linear regression; 10. Dimensionality reduction with principal component analysis; 11. Density estimation with Gaussian mixture models; 12. Classification with support vector machines.
Autoren-Porträt von Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Marc Peter Deisenroth is DeepMind Chair in Artificial Intelligence at the Department of Computer Science, University College London. Prior to this, he was a faculty member in the Department of Computing, Imperial College London. His research areas include data-efficient learning, probabilistic modeling, and autonomous decision making. Deisenroth was Program Chair of the European Workshop on Reinforcement Learning (EWRL) 2012 and Workshops Chair of Robotics Science and Systems (RSS) 2013. His research received Best Paper Awards at the International Conference on Robotics and Automation (ICRA) 2014 and the International Conference on Control, Automation and Systems (ICCAS) 2016. In 2018, he was awarded the President's Award for Outstanding Early Career Researcher at Imperial College London. He is a recipient of a Google Faculty Research Award and a Microsoft P.hD. grant.
Bibliographische Angaben
- Autoren: Marc Peter Deisenroth , A. Aldo Faisal , Cheng Soon Ong
- 2020, 398 Seiten, mit farbigen Abbildungen, Maße: 18 x 25,4 cm, Kartoniert (TB), Englisch
- Verlag: Cambridge University Press
- ISBN-10: 110845514X
- ISBN-13: 9781108455145
- Erscheinungsdatum: 01.04.2020
Sprache:
Englisch
Pressezitat
'This book provides great coverage of all the basic mathematical concepts for machine learning. I'm looking forward to sharing it with students, colleagues, and anyone interested in building a solid understanding of the fundamentals.' Joelle Pineau, McGill University, Montreal
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