Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
Stopping: To understand this, consider the below example: Here, the training error is continuously decreasing with respect to time. On the other hand, the dev set error is decreasing initially before increasing after a few iterations. We can stop the training at the point where the dev set error