Keras and TensorFlow are both open-source software libraries for machine learning.There are also some
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.
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.
Tensorflow use cases