This project is originally developed by Google, and hosts a galaxy of tools, libraries, and community resources to help developers easily build and deploy ML-powered applications.
eras is an open-source neural network library developed in Python which runs on the top of Theano or Tensorflow.
A deep learning framework that comes with an expressive architecture, extensible code, and enviable processing speed.
With Pytorch, it is possible to build complex architectures as it uses dynamic computation, unlike other deep learning frameworks which use static computation methods.
It is an open-source deep-learning tool suitable for flexible research prototyping and production.
Fast.ai is a layered API framework that facilitates practitioners to work with both high level as well as low-level components.
Eclipse Deeplearning is an open-source suite of tools for running deep learning models on Java Virtual Machine and it is the only tool that allows interoperability of Java.
This open-source Python library is meant for fast numerical computation and can perform efficient symbolic differentiation using GPU.
Create statically typed dynamic neural networks from the map and other higher-order functions.
A distributed deep learning library for Apache spark, it provides tools to run deep learning applications as standard Spark programs.