Mathematical Theories of Machine Learning – Theory and Applications

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Mathematical Theories of Machine Learning – Theory and Applications

by Sitharama S. Iyengar; Bin Shi. 

Springer Nature, pp 104, Published by Springer, June 2019

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  • – Provides a thorough look into the variety of mathematical theories of machine learning
  • – Presented in four parts, allowing for readers to easily navigate the complex theories
  • – Includes extensive empirical studies on both the synthetic and real application time series data