Machine Learning & Training

What Is Stochastic Gradient Descent?

Stochastic gradient descent (SGD) is a variant of gradient descent that estimates the gradient from a single example or a small subset of data at each step. This makes updates faster and less memory-intensive than using the entire dataset. The added randomness can help the model escape shallow local minima during training.