Trusted-AI / AIX360
Interpretability and explainability of data and machine learning models
Why this job: matched by what the repo talks about: learn, model, data, machine
What it does
The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datasets and machine learning models. The AI Explainability 360 Python package includes a comprehensive set of algorithms that cover different dimensions of explanations along with proxy explainability metrics. The AI Explainability 360 toolkit supports tabular, text, images, and time series data.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 2 months ago
- Stars
- 1,808
- +1 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.3.0
- Released 3 years ago
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 43% closed
- 45 still open
- Pull requests
- 99 merged
- 16 waiting
- Releases
- 3
- 0 in the last year
- Contributing guide (opens in new tab)
- Security policy (opens in new tab)
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
- R <1%
- Dockerfile <1%
- Shell <1%
Topics
- explainable-ai
- explainable-ml
- trusted-ai
- trusted-ml
- machine-learning
- deep-learning
- codait
- artificial-intelligence
- explainabil
- xai
- ibm-research
- ibm-research-ai
Project record
- JobEvals and observability
- StatusListed
- Commits674
- Forks329
- Watching54
- Stars in 28 days+3
- CreatedJul 11, 2019
- First seen by usNov 7, 2026
- CheckedNov 8, 2026