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🤖 ML pipeline
Open source platform for the machine learning lifecycle
Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Apache Spark - A unified analytics engine for large-scale data processing
Apache Beam is a unified programming model for Batch and Streaming data processing.
AI's query engine - Platform for building AI that can learn and answer questions over federated data.
A light-weight, flexible, and expressive statistical data testing library
scikit-learn: machine learning in Python
Streamlit — A faster way to build and share data apps.
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
LlamaIndex is the leading framework for building LLM-powered agents over your data.
Open standard for machine learning interoperability
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
The interactive graphing library for Python ✨
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Pipelines: Versatile, UI-Agnostic OpenAI-Compatible Plugin Framework
Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]