Explain Keras Architecture?

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result as fast as possible is key to doing good research.

Keras High-Level API handles the way we make models, defining layers, or set up multiple input-output models. In this level, Keras also compiles our model with loss and optimizer functions, and training process with fit function. Keras doesn’t handle Low-Level API such as making the computational graph, making tensors or other variables as it has been handled by the “backend” engine.

Keras Sequential Models:

The Sequential model API is a way of creating deep learning models where an instance of the Sequential class is created and model layers are created and added to it.