what-if-tool
An interactive visual interface for exploring and debugging black-box machine learning models without writing code.
What is what-if-tool?
The What-If Tool is an open-source visualization tool for interpreting and debugging machine learning models. It provides an interactive interface to explore model predictions, analyze performance across data subsets, and investigate fairness issues without requiring any coding. The tool integrates with TensorBoard, Jupyter notebooks, and Google Colab, supporting TensorFlow models, AI Platform Prediction, and custom prediction functions.
Machine learning researchers, data scientists, and model developers who need to debug, interpret, or explain black-box models. It's also suitable for non-technical stakeholders who want to understand model behavior on specific datasets.
Developers choose the What-If Tool for its comprehensive, code-free visualization capabilities that go beyond basic metrics. It uniquely combines counterfactual analysis, interactive data editing, fairness evaluation, and attribution visualization in a single, user-friendly interface.
Overview
Source code/webpage/demos for the What-If Tool
Use Cases
Best For
- Debugging classification or regression models by exploring mispredictions and edge cases
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