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GitHub / explainX / explainx
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/explainX%2Fexplainx
Stars: 393
Forks: 54
Open Issues: 6
License: mit
Language: Jupyter Notebook
Repo Size: 61.2 MB
Dependencies:
21
Created: almost 4 years ago
Updated: 13 days ago
Last pushed: 3 months ago
Last synced: 9 days ago
Commit Stats
Commits: 173
Authors: 4
Mean commits per author: 43.25
Development Distribution Score: 0.416
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/explainX/explainx
Topics: aws-sagemaker, bias, blackbox, explainability, explainable-ai, explainable-artificial-intelligence, explainable-ml, explainx, interpretability, interpretable-ai, interpretable-machine-learning, machine-learning, machine-learning-interpretability, scikit-learn, transparency, xai
Funding links: https://patreon.com/explainxai
Files
Dependencies
- catboost ==0.21
- cvxopt ==1.2.4
- dash ==1.12.0
- dash-editor-components ==0.0.2
- dash_bootstrap_components ==0.10.2
- dash_core_components ==1.10.0
- dash_html_components ==1.0.3
- dash_table ==4.7.0
- h2o ==3.30.1.3
- jupyter_dash ==0.2.1.post1
- numpy ==1.18.1
- pandas ==1.0.4
- pandasql ==0.7.3
- plotly ==4.5.1
- pyrebase *
- pytest *
- scikit-learn ==0.22.1
- scipy ==1.4.1
- shap ==0.37.0
- tqdm ==4.47.0
- xgboost ==1.0.2