DreamSoul-AI/ColDA
Collaborative Data Analysis for All
This project helps data scientists and machine learning engineers perform collaborative data analysis and machine learning across different organizations without directly sharing raw data. You input distributed datasets held by multiple parties, and it outputs a collectively trained machine learning model and aggregated results, preserving data privacy. This is for professionals who need to build models using sensitive data residing in different silos.
No commits in the last 6 months.
Use this if you need to train machine learning models on data that is distributed across several organizations or departments, and you cannot directly combine the raw data due to privacy, security, or regulatory concerns.
Not ideal if all your data resides in a single, accessible location, or if you are looking for a simple, single-machine data analysis tool without collaborative features.
Stars
19
Forks
4
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Jun 15, 2023
Commits (30d)
0
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