sequential , functional and model subclassing API in Keras _ day 14

In our last blog on day 13, we explained what’s Keras and we showed a code example which was using the Sequential API but did not discuss its API type. Understanding Keras APIs and Their Use Cases In our previous blog post on Day 13, we introduced Keras and provided a code example using the Sequential API. In this post, we will delve into the different types of Keras APIs: Sequential, Functional, and Model Subclassing. We will explain each API, its inventor, appropriate use cases, and whether they can be used interchangeably. We will also analyze the code examples provided to illustrate the differences between these approaches. Sequential API Inventor: François Chollet, the creator of Keras. Overview: The Sequential API is the simplest and most straightforward way to build a neural network in Keras. It allows you to create a model layer-by-layer in a linear stack. Use Cases: – Simple models with a single input and a single output.- Beginners and quick prototyping.- Basic feedforward neural networks and simple CNNs. Mathematical Foundation: The Sequential API models are compositions of functions, where each layer L_i applies a transformation f_i:

    \[y = L_n \circ L_{n-1} \circ \ldots \circ L_1(x)\]

This means the output…

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