The Ray Ecosystem

Amazon

Scaling AI and Machine Learning Workloads with Ray on AWS

Google Cloud Platform

Building a ML Platform on Ray and Google Kubernetes Engine

Analytics Zoo

Open Source Big Data Platform

Arize

Observability Platform for ML practitioners

Classy Vision

End-to-end Framework for Image and Video Classification

Dask

Flexible parallel computing library for analytics

Flambé

An ML framework to accelerate research and its path to production

Flyte

Scalable and flexible workflow orchestration

Horovod

Open-source framework for distributed deep learning training

Hugging Face Transformers

Natural Language Processing for Pytorch and TensorFlow 2.0

John Snow Labs

Open source AI and NLP for healthcare

Light GBM

Distributed gradient-boosting ML framework

Ludwig

Declarative machine learning framework

Mars

Tensor-based unified framework for large-scale data computation

Modin

Open source project to speed data preparation and manipulation

Prefect

Open source workflow orchestration platform in Python

Pycaret

Open-source, low-code library in Python to automate ML workflows

Pytorch Lighting

Open-source, low-code library in Python to automate ML workflows

Scikit Learn

Data analysis library for ML in Python

Seldon

Open source Python library for ML model inspection and interpretation.

Apache Spark

Easily use Spark inside a Ray program to read, process or transform data

SpaCy

Open-source software library for advanced NLP

Weights & Biases

Developer-first MLOps platform

Whylabs

AI observability platform and monitoring solution

XGBoost

Gradient boosting library for classification and regression