- Dropout means dropping out some of the nodes of the neural network to avoid Overfitting
- This is done randomly based on given probability
- Dropout can be thought of ensemble of multiple networks
- One way to solve Overfitting is ensemble of multiple neural networks
- But for a big neural network, it is inefficient and time consuming
- So one of the way is to use Dropout.
- Dropout randomly drops out nodes on the training time from the parent network
- Hence create different models for each batch