A toolkit for interpreting and explaining machine learning models, providing insights into model predictions and behavior using LIME, SHAP, and other XAI techniques.
This repository is part of the Eation5 GitHub profile transformation project, showcasing advanced AI/ML engineering skills in Python.
- Core Functionality: Detailed implementation of Explainable AI Toolkit.
- Technology Stack: Built with Python and leveraging key libraries/frameworks such as xai, explainable-ai, machine-learning.
- Scalability: Designed for high performance and scalability in enterprise-level AI applications.
Clone the repository and follow the instructions in the docs/ directory to set up your environment and run the examples.
Contributions are welcome! Please refer to CONTRIBUTING.md for guidelines.
This project is licensed under the MIT License - see the LICENSE file for details.