Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks.
intensive (imagining storing all the data in memory for the calculation) Stochastic Gradient Descent In this approach, the algorithm chooses a single observation, at random, for the calculation of gradient at each step. The parameter values are then updated based on the gradient. This approach is