Machine Learning Tools

TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

freemium

Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.

Deep Learning and AI accessible to everyone

Open source deep learning platform that provides a seamless path from research prototyping to...

Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.

Datatron automates the deployment, monitoring, governance, and validation of your machine learning models in scikit-learn, TensorFlow, Keras, Pytorch, R, H20 and SAS

MLKit is a simple machine learning framework written in Swift.

Machine Learning Operationalization

Developer tools for deep learning research