A curated list of awesome responsible machine learning resources.
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Updated
Aug 15, 2024
A curated list of awesome responsible machine learning resources.
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
H2O.ai Machine Learning Interpretability Resources
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 @ ms8909@nyu.edu
Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
An interpretable machine learning pipeline over knowledge graphs
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
Article for Special Edition of Information: Machine Learning with Python
Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539
TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning
Rule Extraction from Bayesian Networks
Overview of machine learning interpretation techniques and their implementations
INVASE: Instance-wise Variable Selection . For more details, read the paper "INVASE: Instance-wise Variable Selection using Neural Networks," International Conference on Learning Representations (ICLR), 2019.
Demonstration of InterpretME, an interpretable machine learning pipeline
This project contains the data, code and results used in the paper title "On the relationship of novelty and value in digitalization patents: A machine learning approach".
XMLX GitHub configuration
XMLX GitHub configuration
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