Keras Model Sequential API VS Functional API

Keras Deep Learning library helps to develop the neural network models fast and easy. There are two ways to build a model in Keras — Sequential and Functional. Let me explain.

Sequential API allows you to create models layer-by-layer by stacking them. It is limited in that it does not allow you to create models that share layers or have multiple inputs or outputs.

Example Code:

And now lets plot your model using keras utils.

As you can see, Sequential API create model and stacking them together layer by layer. Sequential API is very easy to create deep learning model in most of case.

Keras functional API provides a more flexibility as you can easily defines models where layers connect to more than just the previous and next layers, and you can connect layers to any other layers. As a result, you can create complex network such as Residual Network.

Example Code:

Plot functional model using keras utils.

As you can see, Functional API let us to make layers more flexible.

Example Code :

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