Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

☁️ Build multimodal AI applications with cloud-native stack

A high-throughput and memory-efficient inference and serving engine for LLMs

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

An orchestration platform for the development, production, and observation of data assets.

Machine Learning Engineering Open Book

Always know what to expect from your data.

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, and modular.

Run any open-source LLMs, such as Llama 2, Mistral, as OpenAI compatible API endpoint in the cloud.

Turns Data and AI algorithms into production-ready web applications in no time.

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

🚀 Build and manage real-life ML, AI, and data science projects with ease!

The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!

The Open Source Feature Store for Machine Learning

ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)

🔮 SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, FEDML Nexus AI (https://fedml.ai) is your generative AI platform at scale.