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1. Bank-Customer-Churn-Prediction Bank-Customer-Churn-Prediction Public

   Banks lose customers silently. Without a model, the retention team has no idea who is about to leave until it is too late. Goal: flag at-risk customers early enough to act. Built a full ML pipeline…

   Jupyter Notebook 4

2. Time-Series-Forecasting-K-Nearest-Neighbors Time-Series-Forecasting-K-Nearest-Neighbors Public

   Challenge: predict the optimal moment to sell a stock for profit. Implemented TSFKNN in Python from scratch on TEZNY daily prices. A Pareto frontier mapped the efficient risk-return trade-off at ea…

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