
TensorFlow
An end-to-end open source platform for machine learning.
Discover the strongest tools and workflows for deploy machine learning models.

An end-to-end open source platform for machine learning.

A sequence modeling toolkit for research and production.

Ray is an open-source AI compute engine for scaling AI and Python applications.

.NET Standard bindings for Google's TensorFlow, enabling C# and F# developers to build, train, and deploy machine learning models.

Real-time machine learning deployment with enhanced observability for any AI application or system, managed your way.

Serverless infrastructure for high-performance ML model inference and deployment.

A fully managed machine learning service to build, train, and deploy ML models with fully managed infrastructure, tools, and workflows.

The Pythonic framework for high-scale data science and MLOps orchestration.

The open-source standard for the complete machine learning lifecycle and LLM management.

The Open-Source Collaborative MLOps Platform for Reproducible Machine Learning.

Build and deploy production-grade AI and data science web applications in pure Python.

PostgresML is a Postgres extension that enables you to run machine learning models directly within your database.

Run and fine-tune machine learning models with a production-ready API.

The fastest way to build and share data apps.

Open-source MLOps platform for automated model serving, monitoring, and explainability in production.

The infrastructure platform for AI builders, maximizing AI potential at enterprise scale.

Build, deploy, and govern all types of AI across all your data with enterprise-grade security and scalability.

Architecting Enterprise AI and Scalable Data Ecosystems for the Agentic Era.