conda create --name exp-tracking-env python=3.9

conda activate exp-tracking-env

cd 02-experiment-tracking

pip install -r requirements.txt

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

git clone https://github.com/mage-ai/mlops.git
cd mlops

./scripts/start.sh

pipenv shell
pipenv sync # or pipenv sync --dev

gunicorn --bind=0.0.0.0:9696 predict:app

python test.py

docker build -t ride-duration-prediction-service:v1 .

docker run -it --rm -p 9696:9696  ride-duration-prediction-service:v1

cd /workspaces/mlops-zoomcamp/05-monitoring/taxi_monitoring
conda activate model_monitoring

docker compose up --build