Dropout & Regularization in DL

Summary

Randomly zeroing out neurons during training to prevent co-adaptation and overfitting — one of the simplest and most effective regularization techniques in deep learning.

• 1Add dropout to a network and observe its effect on train vs. validation loss.
• 2Learn typical dropout rates for different layer types.
• 3Understand why dropout is disabled at inference time.