Project Overview: This project applies supervised machine learning models to predict postpartum depression (PPD) using a Kaggle survey dataset. Three models were implemented: Logistic Regression, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The goal is to demonstrate a full ML workflow including preprocessing, exploratory data analysis, model training, evaluation, and interpretation.
Repository Structure: LICENSE — MIT open-source license README.md — this project overview and instructions ppd.py — main Python script containing preprocessing, model training, and evaluation plots.png — output plots (F1, Accuracy, Precision) postnatal.data.csv — original dataset requirements.txt — Python dependencies for reproducibility results - summary