Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
Gradient Descent We saw in course 1 how vectorization can help us to effectively work with ‘m’ training examples. We can get rid of explicit for loops and make the training phase faster. So, we take the training examples as: Where X is the vectorized input and Y is their corresponding outputs. But