Google What-If Tool
A code-free way to probe, visualize, and analyze machine learning models.
Overview
The What-If Tool is an interactive feature of TensorBoard that allows users to analyze and visualize the behavior of machine learning models without writing any code. It enables exploration of model performance on a dataset, investigation of counterfactuals, and assessment of algorithmic fairness. The tool is designed to be accessible to a broad audience, including developers, researchers, and product managers.
✨ Key Features
- Interactive visualization of model predictions
- Counterfactual analysis to see how predictions change with input modifications
- Performance analysis across different subgroups of data
- Algorithmic fairness assessment using various metrics
- Integration with TensorBoard, Jupyter, and Colab notebooks
🎯 Key Differentiators
- Completely code-free interactive interface
- Strong focus on visual exploration and 'what-if' scenarios
- Integration with the broader TensorFlow and Google AI ecosystem
Unique Value: Provides a powerful, code-free, and interactive way to understand machine learning model behavior and assess fairness.
🎯 Use Cases (4)
✅ Best For
- Analyzing fairness in binary classification models for smile detection
- Detecting misclassifications in multi-class classification models
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Automated, large-scale bias mitigation in production pipelines
- Deep quantitative analysis requiring programmatic access to all metrics
🏆 Alternatives
Its primary advantage is its ease of use for non-programmers and its strong visualization capabilities for exploring counterfactuals.
💻 Platforms
✅ Offline Mode Available
🔌 Integrations
💰 Pricing
Free tier: Fully open-source and free to use.
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