Regularization in Deep Learning
(Sprache: Englisch)
Regularization in Deep Learningdelivers practical techniques to help you build more adaptable deep learning model. Along with exploring strategies for architecture, objective function, and optimisation, you will get just enough of the...
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Regularization in Deep Learningdelivers practical techniques to help you build more adaptable deep learning model. Along with exploring strategies for architecture, objective function, and optimisation, you will get just enough of the theory and mathematics behind regularisation to understand the new research emerging in this important area.
Autoren-Porträt von Liu Peng
Peng Liuis an experienced data scientist focusing on applied research and development of high-performance machine learning models in production. He holds a Ph.D. in Statistics from the National University of Singapore, and teaches advanced analytics courses as an adjunct lecturer in universities. He specialises in the statistical aspects of deep learning.
Bibliographische Angaben
- Autor: Liu Peng
- 2023, 275 Seiten, Maße: 18,7 x 23,5 cm, Taschenbuch, Englisch
- Verlag: Manning
- ISBN-10: 1633439615
- ISBN-13: 9781633439610
- Erscheinungsdatum: 25.09.2023
Sprache:
Englisch
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