What is Keras ?

Deep learning for humans.

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. Keras also gives the highest priority to crafting great documentation and developer guides.

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 and Autograph optimizations, and are easier to deploy across every surface (server, mobile, browser, embedded) thanks to TF Serving, TF Lite, and TF.js.

Exascale machine learning.

Built on top of the TensorFlow platform, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy.

Deploy anywhere.

Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

A vast ecosystem.

Keras is a central part of the tightly-connected TensorFlow ecosystem, covering every step of the machine learning workflow, from data management to hyperparameter training to deployment solutions.

State-of-the-art research.

Keras is used by CERN, NASA, NIH, and many more scientific organizations around the world (and yes, Keras is used at the LHC). Keras has the low-level flexibility to implement arbitrary research ideas while offering optional high-level convenience features to speed up experimentation cycles.

Open source