What are the key optimization algorithms used in deep learning?

What are the key optimization algorithms used in deep learning?

Some key optimization algorithms include Stochastic Gradient Descent (SGD), Adam, RMSprop, and Adagrad.

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 Adam over SGD?

Adam generally converges faster than SGD and is more efficient in terms of computation, especially for large datasets.

Are there any disadvantages to using Adam?

Yes, Adam can sometimes lead to suboptimal solutions and may not generalize as well as SGD in certain cases.