A Gentle Introduction to Dropout for Regularizing Deep Neural Networks
Deep learning neural networks are likely to quickly overfit a training dataset with few examples. Ensembles of neural networks with different model configurations are known to reduce overfitting, but require the additional computational expense of training and maintaining multiple models. A single model can be used to simulate having a large number of different network … Continue reading A Gentle Introduction to Dropout for Regularizing Deep Neural Networks
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