Question - What is the meaning of dropout in Deep Learning?
Answer -
Dropout is a technique that is used to avoid overfitting a model in Deep Learning. If the dropout value is too low, then it will have minimal effect on learning. If it is too high, then the model can under-learn, thereby, causing lower efficiency.