Gradient Descent, Data Science, Data Visualization, Deep Learning, Machine Learning.
computing the gradient over the entire dataset can be very computationally expensive. In such cases, SGD can be used to update the model parameters using a mini batch of data points, which can significantly reduce the computation time. Non-convex optimization problems: In non-convex optimization