
imodels
by csinva (personal account)
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible). (description from the project’s GitHub page)
Repository facts
- Stars
- 1,629
- Forks
- 148
- Open issues and pull requests
- 8
- Primary language
- Jupyter Notebook
- License
- MIT License (MIT)
- Owner
- csinva · Personal account
- Created
- Jul 4, 2019
- Last push
- Oct 16, 2026
Topics
Related projects
Projects that share this one’s GitHub topics.
Rank 3,897: microsoft/responsible-ai-toolbox
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. Thes…
1,847 starsTypeScriptMITLast push Oct 17, 2026
Rank 1,165: interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
6,962 starsC++MITLast push Oct 18, 2026
Rank 5,183: EthicalML/xai
XAI - An eXplainability toolbox for machine learning
1,269 starsPythonMITLast push Nov 29, 2025
Rank 2,254: microsoft/tensorwatch
Debugging, monitoring and visualization for Python Machine Learning and Data Science
3,478 starsJupyter NotebookMITLast push Mar 30, 2026
Rank 8,914: mdipietro09/DataScience_ArtificialIntelligence_Utils
Examples of Data Science projects and Artificial Intelligence use-cases
561 starsJupyter NotebookNo license file detectedLast push Jul 25, 2023
Rank 7,714: HunterMcGushion/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
704 starsPythonMITLast push Jan 20, 2021