Gradient Descent, Gradient Boosting.
Computes one data point at a time. Converges to local minimum of the cost function. Computationally efficient. 3. Mini-batch gradient descent — Computes small batch of data points. Compromise between batch gradient descent and stochastic gradient descent. Faster convergence than batch gradient