Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
Recognizing the importance of initialization in complex neural networks Recognizing the difference between train/validation/test sets Diagnosing the bias and variance issues in our model Learning when and how to use regularization methods such as dropout or L2 regularization Understanding