COMP 3610 Assignment 4

Project files

• assignment4.ipynb
• app.py
• test_app.py
• Dockerfile
• docker-compose.yml
• requirements.txt
• README.md
• .gitignore
• .dockerignore
• models/

Python version

Use Python 3.11.

Install

python -m pip install --upgrade pip setuptools wheel python -m pip install -r requirements.txt

Notebook workflow

1. Run assignment4.ipynb
2. Let the notebook download and process the data
3. Train the two regression models
4. Log the runs in MLflow
5. Register the best model
6. Save the best model into models/

Run the API

uvicorn app:app --reload

Run the tests

pytest -q

Run MLflow UI

mlflow ui --backend-store-uri sqlite:///mlflow.db

Docker

docker build -t taxi-tip-api . docker run -p 8000:8000 taxi-tip-api

Docker Compose

docker compose up --build

Swagger docs