Web Reference: class Adadelta: Optimizer that implements the Adadelta algorithm. class Adafactor: Optimizer that implements the Adafactor algorithm. class Adagrad: Optimizer that implements the Adagrad algorithm. class Adam: Optimizer that implements the Adam algorithm. class AdamW: Optimizer that implements the AdamW algorithm. Jul 23, 2025 · Optimizers adjust weights of the model based on the gradient of loss function, aiming to minimize the loss and improve model accuracy. In TensorFlow, optimizers are available through tf.keras.optimizers. You can use these optimizers in your models by specifying them when compiling the model. An 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 the optimizer will be used.
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