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        "description": "# fairkit-learn fairness toolkit\n\nFairkit-learn is an open-source, publicly available Python toolkit designed\nto help data scientists evaluate and explore machine learning models with\nrespect to quality and fairness metrics simultaneously.\n\nFairkit-learn builds on top of [scikit-learn](https://scikit-learn.org/stable/), the state-of-the-art tool suite\nfor data mining and data analysis, and [AI Fairness 360](https://aif360.mybluemix.net/), the state-of-the-art\nPython toolkit for examining, reporting, and mitigating machine learning bias\nin individual models. \n\nFairkit-learn supports all metrics and learning algorithms available in scikit-learn and AI Fairness\n360, and all of the bias mitigating pre- and post-processing algorithms available in AI Fairness 360, and provides extension points to add more metrics and algorithms.\n\n# Installation\n\nTo install fairkit-learn, run the following command:\n\n``` pip install fairkit-learn==1.0```\n\n# Using fairkit-learn\n\nSample code for how to use fairkit-learn can be found in the examples\nfolder in the repo.\n\n\n",
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