Gradient Descent, Machine Learning, Neural Networks, Optimization, Linear Regression.
training example individually. It computes the gradient using only one randomly selected training example, making it faster than batch gradient descent. SGD has the advantage of adapting quickly to changing patterns in the data. However, it can exhibit more oscillations and may take longer to