python-kerasHow do I use the Adam optimizer with Python Keras?

The Adam optimizer is a popular optimization algorithm for training deep learning models in Python Keras. It is an extension of the stochastic gradient descent algorithm that is based on adaptive estimation of first-order and second-order moments.

To use the Adam optimizer with Python Keras, you first need to import the Adam optimizer class from the Keras library:

from keras.optimizers import Adam

You then need to instantiate the Adam optimizer object with desired parameters such as learning rate, decay rate, and momentum:

opt = Adam(lr=0.001, decay=1e-6, momentum=0.9)

Finally, you need to compile your model with the Adam optimizer object:

model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])

Code explanation

1. from keras.optimizers import Adam: This imports the Adam optimizer class from the Keras library.
2. opt = Adam(lr=0.001, decay=1e-6, momentum=0.9): This instantiates the Adam optimizer object with the given parameters.
3. model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy']): This compiles the model with the Adam optimizer object.

Helpful links

• Keras Documentation - Optimizers
• Understanding the Concept of Learning Rate Decay

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