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Optimization 본문
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Udemy The Complete Neural Network Bootcamp 참고
Optimization
- batch gradient descent
- take all the samples in one iteration = 전체 사용해 update
- number of iterations per epoch = 1
- stochastic gradient descent
- take one sample at each iteration = 한 sample로 각각 update
- number of iterations per epoch = number of samples
- mini-batch gradient descent
- take the best of both batch and stochastic gradient descent
- number of iterations per epoch = number of samples / batch size
Optimization 변형
Stochastic Gradient Descent with momentum
RMS prop: adaptive learning rate method
Adaptive Moment Estimation Adam
Weight Decay
AMS Grad
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