shap/shap

Lime: Explaining the predictions of any machine learning classifier

Fit interpretable models. Explain blackbox machine learning.

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization

⚡ TabPFN: Foundation Model for Tabular Data ⚡

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained