Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
as small as possible. So, if ε is 10–7, we say it is a great approximation, If ε is 10–5, it is acceptable, and if ε is in the range 10–3, we have to change the approximations and recalculate the weights. And that’s a wrap for module 1! Module 2: Optimization Algorithms The objectives behind this