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Machine Learning with Shallow Neural Networks

In: Neural Networks and Deep Learning

Author

Listed:
  • Charu Aggarwal

    (International Business Machines, IBM T. J. Watson Research Center)

Abstract

Conventional machine learning often uses optimization and gradient-descent methods for learning parameterized models. Neural networks are also parameterized models that are learned with continuous optimization methods. In all these cases, the machine learning model constructs a loss function in closed form, and gradient descent is used in order to learn the optimal parameters.

Suggested Citation

  • Charu Aggarwal, 2023. "Machine Learning with Shallow Neural Networks," Springer Books, in: Neural Networks and Deep Learning, edition 2, chapter 0, pages 73-117, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-29642-0_3
    DOI: 10.1007/978-3-031-29642-0_3
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