About this document
How To Reduce Overfitting With Dropout Regularization in Keras by Roque Caicedo is a document available to read on EtoBox.
The document discusses how to reduce overfitting in neural networks using dropout regularization in Keras. It explains how to add dropout layers between dense, convolutional, and recurrent layers. Adding dropout probabilistically removes activations from layers during training, making the model more robust. The tutorial provides examples of implementing dropout with MLPs, CNNs, and RNNs.
- Author
- Roque Caicedo
- Language
- EN