Top 5 Python Shap Projects
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mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
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explainerdashboard
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Project mention: Show HN: Web App with GUI for AutoML on Tabular Data | news.ycombinator.com | 2023-08-24Web App is using two open-source packages that I've created:
- MLJAR AutoML - Python package for AutoML on tabular data https://github.com/mljar/mljar-supervised
- Mercury - framework for converting Jupyter Notebooks into Web App https://github.com/mljar/mercury
You can run Web App locally. What is more, you can adjust notebook's code for your needs. For example, you can set different validation strategies or evalutaion metrics or longer training times. The notebooks in the repo are good starting point for you to develop more advanced apps.
Project mention: Help! Interviewing for ML and modern CV positions (plus a ML model explainer dashboard) | /r/OMSCS | 2023-05-11
Just for some respite from the discussion of our soon-to-be AI overlords (LLMs), I'm one of the contributors to an open-source Python package, Xplainable (https://github.com/xplainable/xplainable). Xplainable is a novel (structured) machine learning algorithm that's inherently explainable, as opposed to being a post-hoc explainer (like SHAP or Lime).
Index
What are some of the best open-source Shap projects in Python? This list will help you:
Project | Stars | |
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1 | mljar-supervised | 2,929 |
2 | explainerdashboard | 2,224 |
3 | FastTreeSHAP | 492 |
4 | powershap | 175 |
5 | xplainable | 52 |
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