Data Science Notebooks

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Interactive code examples/posts

Open Source

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

Open Source

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.

Open Source freemium

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.

RunKit notebooks are interactive javascript playgrounds connected to a complete node environment right in your browser. Every npm module pre-installed.

Machine Learning Operationalization

Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.

Developer tools for deep learning research

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

A collaboration platform for data scientists

The open-source, web-based thinking tool that facilitates effective thinking for solving problems.

Open Source freemium $4.0 / Monthly

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