What is a key characteristic of the Keras Functional API?

The Keras Functional API is designed to allow for the construction of complex neural network architectures that can accommodate multiple inputs and outputs. This characteristic is particularly valuable in scenarios where models need to handle multiple feature sets or produce various types of predictions simultaneously, such as in multi-task learning situations.

With this API, developers can create models that may have shared layers, branched architectures, or even models that combine outputs from different sources. This flexibility is not available in simpler APIs, which typically focus on single input-output configurations. Hence, being able to handle multiple inputs and outputs is a fundamental advantage of the Keras Functional API that facilitates more sophisticated model design and enhances its applicability to a broader range of machine learning tasks.