July 2017
Beginner to intermediate
442 pages
10h 8m
English
Content preview from Statistics for Machine Learning
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Optimization of neural networks
Various techniques have been used for optimizing the weights of neural networks:
- Stochastic gradient descent (SGD)
- Momentum
- Nesterov accelerated gradient (NAG)
- Adaptive gradient (Adagrad)
- Adadelta
- RMSprop
- Adaptive moment estimation (Adam)
- Limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS)
In practice, Adam is a good default choice; we will be covering its working methodology in this section. If you cannot afford full batch updates, then try out L-BFGS:
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