Template MLOps and Data Science Project

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• MLFlow for Model Tracking and Management.
• Minio Open Source S3 Storage for storing Artifacts Model Machine Learning.
• Implement PostgreSQL as Database for Storing Metadata MLFLow.

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How to Run:

make virtual environment for python:

python -m venv _venv

activate virtual environment:

./_venv/Scripts/activate

Install requirements:

pip install -r requirements.txt

Running Docker compose:

docker compose up -d

after all services in docker compose is already running, then open other terminal and try running pipeline in local machine with use

python run_pipeline.py

After all steps done you can check it:

• Minio: http://localhost:9000
• PG Admin: http://localhost:5050
• MLFlow Dashboard: http://localhost:5000

If you don't know user and password you can check configuration in .env or docker-compose.yml