6009CMD-ANNs-Churn_Prediction

Customer churn prediction coursework for 6009CMD Artificial Neural Networks.

This repo is structured around two main notebooks:

EDA_Churn_Model.ipynb: raw-data audit, cleaning workflow, and baseline models
Model_Implementation.ipynb: Part A MLP, Part B feature engineering, Part B MLP, diagnostics, and final comparison

Repo layout

The Model Implementation notebook depends on artefacts saved by the EDA notebook, critically these are:

Run notebooks from the repo root so relative paths resolve correctly.
The notebooks expect the dataset files already present under Datasets, intitially you can only have Churn.csv, that is the main raw dataset file.