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ML Interactive Demonstrations

Experience AI-powered defect detection through interactive web demos

● Live & Interactive

Demo 1: Synthetic Data Generation

Generate realistic wafer images with configurable defect types and parameters.

Demo 2: CNN Classification

Real-time defect classification using deep learning models.

Demo 3: Bayesian Inference

Uncertainty quantification for rare defect detection.

Demo 4: Yield Prediction

Forecast semiconductor yield based on defect patterns.

Demo 5: Active Learning

Intelligent sample selection for model improvement.

Demo 6: Model Comparison

Benchmark different architectures with live metrics.

Demo 7: Production Pipeline

End-to-end workflow from image to yield prediction.

Want full functionality?

Clone the repository and run the Python demos with GPU acceleration

git clone https://github.com/alovladi007/louis-antoine-portfolio.git
cd defect-detection-ml && python demo.py