Keras

What is Keras?

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.

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. It also has extensive documentation and developer guides.

Iterate at the speed of thought

Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win.

Exascale machine learning

Built on top of TensorFlow 2.0, 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 tighly-connected TensorFlow 2.0 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.

An accessible superpower

Because of its ease-of-use and focus on user experience, Keras is the deep learning solution of choice for many university courses. It is widely recommended as one of the best ways to learn deep learning.

official keras.io


src stackshare.io/keras