What is learning rate optimization in machine learning?

What is learning rate optimization in machine learning?

Learning rate optimization is the process of adjusting the learning rate in training algorithms to improve model performance.

Why is the learning rate so important?

The learning rate determines how quickly a model updates its weights. A rate that's too high can cause overshooting, while too low can slow convergence.

How can I find the best learning rate for my model?

You can use techniques like grid search, random search, or learning rate schedules to find the optimal learning rate.

What are some common learning rate schedules?

Common schedules include step decay, exponential decay, and cyclical learning rates, each adjusting the rate at different training stages.