Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
i.e., Vt = β * V(t-1) + (1 — β) * Θt we include a bias correction term: Vt = [β * V(t-1) + (1 — β) * Θt] / (1 — βt) When t is small, βt will be large, resulting in a smaller value of (1-βt). This will make the Vt value larger ensuring that our predictions are accurate. Gradient Descent with