jphall663 / secure_ML_ideas
Practical ideas on securing machine learning models
☆36Updated 3 years ago
Alternatives and similar repositories for secure_ML_ideas:
Users that are interested in secure_ML_ideas are comparing it to the libraries listed below
- ☆35Updated this week
- Paper and talk from KDD 2019 XAI Workshop☆20Updated 4 years ago
- Python implementation of R package breakDown☆42Updated last year
- Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!☆28Updated 5 years ago
- Content for the Model Interpretability Tutorial at Pycon US 2019☆41Updated 7 months ago
- this repo might get accepted☆28Updated 4 years ago
- Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.☆22Updated 5 years ago
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library☆51Updated 2 years ago
- ☆26Updated 4 years ago
- Know your ML Score based on Sculley's paper☆34Updated 5 years ago
- Proposal Documents for Fairlearn☆9Updated 4 years ago
- Distributed, large-scale, benchmarking framework for rigorous assessment of automatic machine learning repositories, projects, and librar…☆30Updated 2 years ago
- Train multi-task image, text, or ensemble (image + text) models☆45Updated last year
- The fast.ai data ethics course☆15Updated 2 years ago
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated 2 years ago
- Guidelines for the responsible use of explainable AI and machine learning.☆17Updated 2 years ago
- H2OAI Driverless AI Code Samples and Tutorials☆37Updated 4 months ago
- Predict whether a student will correctly answer a problem based on past performance using automated feature engineering☆32Updated 4 years ago
- Python library for Ceteris Paribus Plots (What-if plots)☆20Updated 3 years ago
- State management framework for Data Science & Analytics☆19Updated 5 years ago
- Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/☆27Updated 9 months ago
- FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)☆71Updated 3 years ago
- Notebook demonstrating use of LIME to interpret a model of long-term relationship success☆24Updated 7 years ago
- Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.☆21Updated 2 years ago
- Pipeline Explorer - Explore and analyze millions of pipelines learned using MLBlocks and MLPrimitives.☆17Updated last year
- ☆20Updated 4 years ago
- A scikit-learn compatible estimator based on business-rules with interactive dashboard included☆28Updated 3 years ago
- Data Scientist code test☆19Updated 4 years ago
- Tutorial for a new versioning Machine Learning pipeline☆80Updated 3 years ago
- python tools to check recourse in linear classification☆75Updated 4 years ago