Keras and TensorFlow are both open-source software libraries for machine learning.There are also some differences between the two libraries:

Keras is a higher-level library that provides a more intuitive interface whereas tensorFlow is a lower-level library that provides more flexibility and control.

Level of abstraction

Keras is generally easier to learn and use than TensorFlow, while TensorFlow can be more complex and has a steeper learning curve.

Ease of use

Both Keras and TensorFlow support a wide range of model architectures, but TensorFlow can support more complex models.

Supported models

TensorFlow is more customizable and allows users to define their own operations, while Keras is more opinionated and has less flexibility.


TensorFlow provides tools for deploying models to production environments, such as TensorFlow Serving and TensorFlow Lite, while Keras does not.