eXplainable AI course
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Updated
May 30, 2026 - Jupyter Notebook
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umap-learn
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PENDING Open for contribution: A end-to-end project that combines unsupervised machine learning for customer segmentation with scalable data pipelines. It uses MongoDB for data ingestion, Scikit-learn for clustering and Streamlit for interactive visualization — enabling actionable insights into e-commerce
git data mongodb clustering postgresql pca-analysis t-sne data-pipelines great-expectations umap-learn
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Updated
Jun 14, 2025 - Jupyter Notebook
Detecting process failures in semiconductor fabrication using 590 sensor signals, statistical feature selection, and ensemble ML, applied to the real-world UCI SECOM dataset.
numpy scikit-learn sklearn pandas seaborn xgboost scipy matplotlib statsmodels standardscaler simpleimputer imbalanced-learn umap-learn
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Updated
May 24, 2026 - Jupyter Notebook
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