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Keras

Deep Learning library for Theano and TensorFlow
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What is Keras?

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
Keras is a tool in the Machine Learning Tools category of a tech stack.
Keras is an open source tool with 46.5K GitHub stars and 17.6K GitHub forks. Here鈥檚 a link to Keras's open source repository on GitHub

Who uses Keras?

Companies
84 companies reportedly use Keras in their tech stacks, including Hepsiburada, Wongnai, and Bagelcode.

Developers
342 developers on StackShare have stated that they use Keras.

Keras Integrations

Python, Polyaxon, Deepo, Caffe, and Comet.ml are some of the popular tools that integrate with Keras. Here's a list of all 12 tools that integrate with Keras.

Why developers like Keras?

Here鈥檚 a list of reasons why companies and developers use Keras
Keras Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Keras in their tech stack.

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 559.8K views
atUber TechnologiesUber Technologies
TensorFlow
TensorFlow
Keras
Keras
PyTorch
PyTorch

Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details鈥攆or instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA鈥檚 CUDA toolkit.

Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo鈥檚 deep learning toolkit which makes it easier to start鈥攁nd speed up鈥攄istributed deep learning projects with TensorFlow:

https://eng.uber.com/horovod/

(Direct GitHub repo: https://github.com/uber/horovod)

See more

Keras's Features

  • neural networks API
  • Allows for easy and fast prototyping
  • Convolutional networks support
  • Recurent networks support
  • Runs on GPU

Keras Alternatives & Comparisons

What are some alternatives to Keras?
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
ML Kit
ML Kit brings Google鈥檚 machine learning expertise to mobile developers in a powerful and easy-to-use package.
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
See all alternatives

Keras's Followers
360 developers follow Keras to keep up with related blogs and decisions.
Peter Shen
osmanhomek
Justin Houghton
i813380
Avani1994
Ramya Yellapragada
Abdallah Bari
Iwan Traeger-Payne
Kaio Giurizatto
Brandon Allen