What are the different optimizers used in deep learning?

What are the different optimizers used in deep learning?

In deep learning, common optimizers include SGD, Adam, RMSprop, and Adagrad. Each has its strengths.

Can you explain how Adam optimizer works?

Adam combines the advantages of two other extensions of SGD: AdaGrad and RMSProp. It computes adaptive learning rates for each parameter.

What are the advantages of using RMSprop over SGD?

RMSprop adjusts the learning rate for each parameter individually, which helps in dealing with non-stationary objectives.

Which optimizer is generally considered the best?

There isn't a one-size-fits-all answer; it depends on the specific problem and dataset. Adam is popular for many tasks.