Vesta is a menstrual cycle prediction project with a training pipeline and a small Flask web app for local use. It trains a Random Forest model and provides cycle start date predictions from recent history.

pip install -r requirements.txt
pip install -e packages/vesta_ml

# Preprocess data (uses packages/vesta_ml/data/raw/cycles.csv or creates sample data)
python packages/vesta_ml/scripts/preprocess.py

# Train models (Random Forest + quantile models)
python packages/vesta_ml/scripts/train.py

# Evaluate and generate plots/metrics
python packages/vesta_ml/scripts/evaluate.py

python packages/vesta_ml/scripts/predict.py --input packages/vesta_ml/data/raw/cycles.csv

python -m flask --app app:create_app --debug run

The app stores data in instance/vesta.db and predicts once six cycles are saved.

Digital Ocean Droplet

• Complete Deployment Guide - $4-6/month
• Includes model training, Docker setup, and optional HTTPS with SSL
• Docker-based with persistent SQLite storage

Your CSV should look like:

start_date,end_date
2023-01-15,2023-01-20
2023-02-12,2023-02-17
2023-03-10,2023-03-16

• Trained model artifacts are saved under packages/vesta_ml/models/random_forest/.
• The scaler is saved under packages/vesta_ml/data/processed/scaler.pkl.
• This project is for educational purposes and is not medical advice.