How Does Dropout Help Overfitting?
How Does Dropout Help Overfitting? Dropout is a regularization technique that prevents neural networks from overfitting. Regularization methods like L1 and L2 reduce overfitting by modifying the cost function. Dropout on the other hand, modify the network itself. It randomly drops neurons from the neural network during training in each iteration. What is dropout in