It is a framework called MADS (Multi-Agents for Data Science) that enables users to perform a systematic data science pipeline with just two inputs. MADS uses multi-agents to automate the entire data science process, allowing users to define their project goals while the agents handle tasks such as data preprocessing, model training, predictions, and generating insights. The framework outputs a trained model, predictions, and a detailed report summarizing the agents’ findings.
MADS is designed to make machine learning accessible to everyone by simplifying the process. Users only need to provide a dataset and define their project objectives. The framework requires Python 3.11.7 or higher and can be installed via pip using the command `pip install pymads`. To use MADS, users must set up a `.env` file containing their API key, either from GROQ or OpenAI, and optionally disable Docker usage by adding `AUTOGEN_USE_DOCKER=”False”` to the file.
The project is open-source and encourages contributions from the community. Users can report issues on GitHub, providing detailed information to help improve the library. MADS is released under the MIT License and acknowledges the contributions of the autogen framework and the broader community. For more information, users can visit the official website, research website, or read the pre-print MADS paper.
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