Gradient Descent, Data Science, Data Visualization, Deep Learning, Machine Learning.
Computes the gradient of the cost function over the entire training set. Updates the model parameters once per iteration. Converges more slowly but steadily towards the minimum of the cost function. Can be more stable than SGD and MBGD, but may take longer to converge. Requires more memory and