PAIR-code/what-if-tool

Health v2 · maintenance only

Adoption not part of the score

1007 stars · 183 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The What-If Tool (WIT) is a visual interface from Google's PAIR team for probing black-box classification and regression ML models without writing code. It runs inside TensorBoard or as a Jupyter/Colab notebook extension, letting users run inference, edit examples, and analyze model performance and fairness across data subsets.

Use cases

• visually probe behavior of a trained ML model
• analyze model fairness across demographic subsets
• compare performance of multiple models side by side
• edit test examples and re-run inference to see what changes
• investigate feature importance and counterfactuals without coding
• explore model predictions in a Jupyter or Colab notebook

When to choose

• you want no-code visual exploration of a trained classifier or regression model
• you need to audit model fairness and performance across data subsets
• you already work in TensorBoard, Jupyter, or Colab
• you want counterfactual what-if analysis of individual predictions

When to avoid

• you need programmatic interpretability methods like SHAP or LIME in a pipeline
• your model is not servable via a Python function, TF Serving, or Cloud AI Platform
• you need real-time production model monitoring rather than interactive analysis
• you work outside the TensorFlow/Python notebook ecosystem

Facets

plugin · maturity maintenance

data-visualization machine-learning testing machine-learning data-visualization artificial-intelligence python browser model-interpretability fairness tensorboard-plugin jupyterlab-extension google-pair no-code model-analysis web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="PAIR-code/what-if-tool")