End-to-end customer churn prediction — EDA, Random Forest, SHAP explainability, and a Streamlit dashboard with real-time predictions.
Climate Trend Analyzer is a data science project that analyzes historical climate data to detect anomalies, visualize trends, and forecast future temperature patterns using Python and Streamlit.
Counterparty exposure and collateral risk analytics covering eligibility assessment, haircut application, collateral sufficiency, concentration monitoring, and stress testing.
Handwritten digit recognition system: three neural architectures (Dense NN, LeNet-5, Custom CNN), Grad-CAM explainability, interactive Streamlit dashboard, 145 tests, Docker, GitHub Actions CI. Python 3.12 · TensorFlow 2.16 · MNIST.
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