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About Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Gradient descent is used to optimize neural networks by iteratively processing training examples to update network parameters downhill towards a minimum. Batch gradient descent processes all examples at once while stochastic gradient descent processes one example at a time. Mini-batch gradient descent processes examples in small batches of 1 to m examples to balance speed of batch processing with frequent parameter updates of stochastic gradient descent. Choosing an optimal mini-batch size can provide the fastest learning in practice.
Detailed Information
| Author: | ['Sharath Poikayil Satheesh'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 1 |
| Language: | English |
| Format: | |
| Price: | FREE |
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