A superpower for developers.
The purpose of Keras is to give an unfair advantage to any developer looking to ship Machine Learning-powered apps.
Keras focuses on debugging speed, code elegance & conciseness, maintainability, and deployability.
When you choose Keras, your codebase is smaller, more readable, easier to iterate on. Your models run faster
thanks to XLA compilation with JAX and TensorFlow, and are easier to deploy across every surface (server, mobile, browser, embedded) thanks to
the serving components from the TensorFlow and PyTorch ecosystems, such as TF Serving, TorchServe, TF Lite, TF.js, and more.