jphall663 / xai_misconceptionsLinks
Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!
☆29Updated 6 years ago
Alternatives and similar repositories for xai_misconceptions
Users that are interested in xai_misconceptions are comparing it to the libraries listed below
Sorting:
- Guidelines for the responsible use of explainable AI and machine learning.☆17Updated 2 years ago
- Practical ideas on securing machine learning models☆36Updated 4 years ago
- Python implementation of R package breakDown☆43Updated 2 years ago
- Paper and talk from KDD 2019 XAI Workshop☆20Updated 5 years ago
- Repo for the ML_Insights python package☆153Updated 7 months ago
- This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.☆119Updated 4 years ago
- Notebook demonstrating use of LIME to interpret a model of long-term relationship success☆24Updated 8 years ago
- Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/☆27Updated last year
- python tools to check recourse in linear classification☆77Updated 4 years ago
- ☆39Updated 6 months ago
- Simplified tree-based classifier and regressor for interpretable machine learning (scikit-learn compatible)☆46Updated 4 years ago
- A Python package for unwrapping ReLU DNNs☆68Updated last year
- Embed categorical variables via neural networks.☆59Updated 2 years ago
- Research code for auditing and exploring black box machine-learning models.☆132Updated 2 years ago
- Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.☆22Updated 5 years ago
- H2OAI Driverless AI Code Samples and Tutorials☆37Updated last year
- FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)☆72Updated 4 years ago
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library☆51Updated 3 years ago
- Python library for Ceteris Paribus Plots (What-if plots)☆26Updated 4 years ago
- Analysis of Categorical Encodings for dense Decision Trees☆41Updated 8 years ago
- ☆103Updated 2 years ago
- General Interpretability Package☆58Updated 2 years ago
- Learning Certifiably Optimal Rule Lists☆176Updated 4 years ago
- ⬛ Python Individual Conditional Expectation Plot Toolbox☆165Updated 5 years ago
- XAI Stories. Case studies for eXplainable Artificial Intelligence☆31Updated 5 years ago
- A machine learning testing framework for sklearn and pandas. The goal is to help folks assess whether things have changed over time.☆104Updated 4 years ago
- State management framework for Data Science & Analytics☆19Updated 6 years ago
- Content for the Model Interpretability Tutorial at Pycon US 2019☆41Updated last year
- simple customizable risk scores in python☆142Updated 2 years ago
- Tutorial for a new versioning Machine Learning pipeline☆80Updated 4 years ago