The main difference between a Sequential model and a Functional API model in Keras is the way in which the models are constructed. A Sequential model is a linear stack of layers, where each layer has exactly one input and one output. This type of model is simple to construct and is suitable for most basic deep learning tasks. On the other hand, a Functional API model is a more flexible and powerful type of model that allows for more complex architectures. It allows for multiple inputs and outputs, as well as the ability to create models with shared layers. This type of model is more suitable for complex tasks such as image classification or natural language processing.
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