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End-to-end credit risk ML system — GradientBoosting vs LightGBM vs Statsmodels comparison, calibrated probabilities, Docker containerized, AWS S3/EC2, CI/CD via GitHub Actions, numpy-only serverless inference on FastAPI/Vercel, React dashboard.
Fun Project -: Playing with the statistics. Main Motto -: Trying to understand the statistics underneath the various most commonly used Machine Learning Models. I have used two library i.e. Stats-Model and Scikit-Learn.