#classification

End-to-end Employee Attrition Prediction system with data analysis, feature engineering, model comparison, explainable AI (SHAP), FastAPI deployment, and Docker.

An end-to-end AI-powered breast cancer diagnosis system using Machine Learning, FastAPI, and Streamlit for real-time cancer risk prediction and healthcare analytics.

Deterministic failure-triage baseline scored against ground truth. Clustering is worth +59.6 macro F1 over the floor; cross-run frequency measurably was not. Project 1 of an AI-in-QA portfolio.

Breast Cancer Classification using Machine Learning

An automated machine learning pipeline that performs EDA, preprocessing, model training, evaluation, and best model selection for classification and regression datasets.