Adam - Keras
https://keras.io/api/optimizers/adamAdam optimization is a stochastic gradient descent method that is based on adaptive estimation of first-order and second-order moments. According to Kingma et al., 2014 , the method is " computationally efficient, has little memory requirement, invariant to diagonal rescaling of gradients, and is well suited for problems that are large in terms of data/parameters ".
Optimizers - Keras
https://keras.io/api/optimizersAn optimizer is one of the two arguments required for compiling a Keras model: You can either instantiate an optimizer before passing it to model.compile () , as in the above example, or you can pass it by its string identifier. In the latter case, the default parameters for …