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Mastering Python for Finance - Second Edition
book

Mastering Python for Finance - Second Edition

by James Ma Weiming
April 2019
Intermediate to advanced
426 pages
11h 13m
English
Packt Publishing
Content preview from Mastering Python for Finance - Second Edition

Optimizers

Optimizers help to tweak the model weights optimally in minimizing the loss function. There are several types of optimizers that you may come across in deep learning:

  • AdaGrad (adaptive gradient)
  • Adam (adaptive moment estimation)
  • LBFGS (limited-memory Broyden-Fletcher-Goldfarb-Shannon)
  • Rprop (resilient backpropagation)
  • RMSprop (root mean square propagation)
  • SGD (stochastic gradient descent)

Adam is a popular choice of optimizer, and is seen as a combination of RMSprop and SGD with momentum. It is an adaptive learning rate optimization algorithm, computing individual learning rates for different parameters.

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Publisher Resources

ISBN: 9781789346466