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Search: DATA-AI
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Showing 10 results from 2,312
aurelio-labs/semantic-router
GitHub Python MIT LicenseSuperfast AI decision making and intelligent processing of multi-modal data.
External source
GitHub
sugarforever/chat-ollama
GitHub TypeScript OtherChatOllama is an open-source AI chatbot that brings cutting-edge language models to your fingertips while keeping your data private and secure.
External source
GitHub
deta/surf
GitHub TypeScript Apache License 2.0Personal AI Notebooks. Organize files & webpages and generate notes from them. Open source, local & open data, open model choice (incl. local).
External source
GitHub
unitycatalog/unitycatalog
GitHub Java Apache License 2.0Open, Multi-modal Catalog for Data & AI
External source
GitHub
vietanhdev/anylabeling
GitHub Python GNU General Public License v3.0Effortless AI-assisted data labeling with AI support from YOLO, Segment Anything (SAM+SAM2/2.1+SAM3), MobileSAM!!
External source
GitHub
microsoft/mcp
GitHub C# MIT LicenseCatalog of official Microsoft MCP (Model Context Protocol) server implementations for AI-powered data access and tool integration
External source
GitHub
argilla-io/distilabel
GitHub Python Apache License 2.0Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.
External source
GitHub
lakesoul-io/LakeSoul
GitHub Java Apache License 2.0LakeSoul is an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.
External source
GitHub
swirlai/swirl-search
GitHub Python Apache License 2.0AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.
External source
GitHub
jupyter-naas/awesome-notebooks
GitHub Jupyter Notebook BSD 3-Clause "New" or "Revised" License[Legacy] Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..
External source
GitHub
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