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Learn about the Functional API and how to build complex Keras models using it
TensorFlow’s Sequential API makes it easy to create linear models by stacking layers one after another. In this setup, each layer’s input is the output of the previous layer. However, when your model needs to handle multiple inputs or outputs, shared layers, or non-linear connections, the Sequential API might not be sufficient. That’s where TensorFlow’s Functional API comes in. It allows you to build more advanced, flexible, and customizable models, enabling you to design complex architectures with ease.
This article will explain:
- What the Functional API is
- How to build a simple model with the Functional API
TensorFlow’s Functional API allows you to create models where layers are connected like a network graph, rather than being just stacked one after another, as in the Sequential API. Think of it like building with LEGO bricks: while the Sequential API would let you stack blocks in a simple column, the Functional API lets you create bridges, towers, and pathways that connect different parts, giving you more creative freedom in designing your model.
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