mercury-explainability is a library with implementations of different state-of-the-art methods in the field of explainability. They are designed to work efficiently and to be easily integrated with the main Machine Learning frameworks.
☆17Jun 18, 2026Updated 2 months ago
Alternatives and similar repositories for mercury-explainability
Users that are interested in mercury-explainability are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- mercury-monitoring is a library to monitor data and model drift☆16Jun 18, 2026Updated 2 months ago
- mercury-robust is a framework to perform robust testing on ML models and datasets. It provides a collection of test that are easy to conf…☆22Jun 18, 2026Updated 2 months ago
- A Python 3 library developed in C++ that enables efficient storage and querying of sets of sets. It can be used to perform fast document …☆13Jun 18, 2026Updated 2 months ago
- Kaggle Heritage Health Prize Challenge☆20Dec 5, 2023Updated 2 years ago
- Record matching and entity resolution at scale in Spark☆36Oct 31, 2023Updated 2 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Spanish data from the AnCora corpus.☆34Updated this week
- ☆14Aug 3, 2021Updated 5 years ago
- ☆13Nov 21, 2021Updated 4 years ago
- The TaskBench500 dataset and code for generating tasks.☆16Jul 16, 2022Updated 4 years ago
- Track how many Twitter followers an account has over time.