K-Nearest Neighbors Kaggle Competition

In this assignment, you will implement a K-Nearest Neighbors (KNN) model from scratch to predict customer churn for a bank. Your goal is to identify customers who are likely to leave the bank based on historical data and submit your predictions in a mini Kaggle competition.

You are provided with a dataset and a starter code to help you get started. Your task is to preprocess the data, implement KNN from scratch, train and evaluate the model, and tune its hyperparameters. Once your model is optimized, you will submit your predictions for ranking on Kaggle.

Please refer to the Kaggle Competition for full competition details and the starter code here to complete the required parts.