What is the learning rate in AI and why is it important?

What is the learning rate in AI and why is it important?

The learning rate is a hyperparameter that controls how much to change the model in response to the estimated error each time the model weights are updated. It's crucial because it affects the speed and quality of the learning process.

How do I choose the right learning rate for my model?

Choosing the right learning rate can be done through experimentation. You can start with a small value and gradually increase it, or use techniques like learning rate schedules or adaptive learning rate methods.

What happens if the learning rate is too high?

If the learning rate is too high, the model may converge too quickly to a suboptimal solution or even diverge, leading to poor performance.

And what if it's too low?

If the learning rate is too low, the training process will be very slow, and the model may get stuck in local minima, resulting in longer training times and potentially suboptimal performance.