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The Top 23 Machine Learning Explainability Open Source Projects

Open source projects categorized as Machine Learning Explainability
Categories > Explainability
Categories > Machine Learning > Machine Learning
Shap ⭐ 21,595
A game theoretic approach to explain the output of any machine learning model.
dependent packages 373total releases 100most recent commit 5 days agopypi shap} Downloads
Awesome Production Machine Learning ⭐ 15,804
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
most recent commit 25 days ago
Interpret ⭐ 5,992
Fit interpretable models. Explain blackbox machine learning.
dependent packages 28total releases 45most recent commit 4 days agopypi interpret} Downloads
Shapash ⭐ 2,547
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
dependent packages 2total releases 37most recent commit 4 months agopypi shapash} Downloads
Responsible Ai Toolbox ⭐ 1,187
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. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
dependent packages 8total releases 6most recent commit 18 days agopypi raiutils} Downloads
Xai ⭐ 1,060
XAI - An eXplainability toolbox for machine learning
total releases 6most recent commit 2 years ago
Flashtorch ⭐ 712
Visualization toolkit for neural networks in PyTorch! Demo -->
total releases 12most recent commit 7 months ago
Awesome Graph Explainability Papers ⭐ 486
Papers about explainability of GNNs
most recent commit 3 months ago
Explainx ⭐ 375
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]
total releases 56most recent commit 3 months ago
Carla ⭐ 216
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
total releases 2most recent commit a year ago
Sage ⭐ 205
For calculating global feature importance using Shapley values.
total releases 5most recent commit 5 months ago
Whitebox ⭐ 184
[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes
most recent commit 9 months ago
Zennit ⭐ 151
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
dependent packages 2total releases 15most recent commit 7 months agopypi zennit} Downloads
Hierarchical Dnn Interpretations ⭐ 119
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
total releases 7most recent commit 3 years ago
Sagemaker Explaining Credit Decisions ⭐ 87
Amazon SageMaker Solution for explaining credit decisions.
most recent commit a year ago
Pytorch_explain ⭐ 80
PyTorch Explain: Logic Explained Networks in Python.
total releases 22most recent commit 10 months ago
Deep Explanation Penalization ⭐ 74
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
most recent commit 3 years ago
Acv00 ⭐ 73
ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based models.
dependent packages 1total releases 8most recent commit 2 years agopypi acv-exp} Downloads
Treeshap ⭐ 72
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
total releases 1most recent commit 3 months ago
Contextual Ai ⭐ 72
Contextual AI adds explainability to different stages of machine learning pipelines - data, training, and inference - thereby addressing the trust gap between such ML systems and their users. It does not refer to a specific algorithm or ML method — instead, it takes a human-centric view and approach to AI.
total releases 2most recent commit 2 years ago
Talktomodel ⭐ 68
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
most recent commit 9 months ago
Awesome Shapley Value ⭐ 63
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
most recent commit 2 years ago
Fat Forensics ⭐ 63
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
total releases 5most recent commit a year ago
The 7 Most Depended On Machine Learning Explainability Open Source Projects
Shap ⭐ 21,595
A game theoretic approach to explain the output of any machine learning model.
dependent packages 373total releases 100latest release December 07, 2023most recent commit 5 days agopypi shap} Downloads
Interpret ⭐ 5,992
Fit interpretable models. Explain blackbox machine learning.
dependent packages 28total releases 45latest release August 26, 2023most recent commit 4 days agopypi interpret} Downloads
Shapash ⭐ 2,547
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
dependent packages 2total releases 37latest release December 08, 2023most recent commit 4 months agopypi shapash} Downloads
Javaanchoradapters ⭐ 6
Getting the Anchors Explainer to work in Different Settings
dependent packages 1total releases 4latest release November 18, 2019most recent commit 6 months ago
The 10 Latest Releases In Machine Learning Explainability Open Source Projects
Shapash ⭐ 2,547
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
dependent packages 2total releases 37latest release December 08, 2023most recent commit 4 months agopypi shapash} Downloads
Shap ⭐ 21,595
A game theoretic approach to explain the output of any machine learning model.
dependent packages 373total releases 100latest release December 07, 2023most recent commit 5 days agopypi shap} Downloads
Bunkatopics ⭐ 43
🗺️ Data Cleaning and Textual Data Visualization 🗺️
total releases 41latest release October 20, 2023most recent commit 3 months ago
Treeshap ⭐ 72
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
total releases 1latest release October 01, 2023most recent commit 3 months ago
Te2rules ⭐ 25
Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.
total releases 16latest release August 31, 2023most recent commit 4 months ago
Interpret ⭐ 5,992
Fit interpretable models. Explain blackbox machine learning.
dependent packages 28total releases 45latest release August 26, 2023most recent commit 4 days agopypi interpret} Downloads
Bhad ⭐ 9
A Python library for Bayesian Anomaly Detection
total releases 9latest release May 30, 2023most recent commit 4 months ago
Sage ⭐ 205
For calculating global feature importance using Shapley values.
total releases 5latest release January 07, 2023most recent commit 5 months ago
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