Deployment and CI/CD

Start here (read): DVC, "CI/CD for Machine Learning" → https://dvc.org/doc/use-cases/ci-cd-for-machine-learning

Goal: Learn the tradeoffs between batch, real-time, and embedded deployment, and build a GitHub Actions pipeline that tests, validates data, and gates model changes on every pull request.

Do:

1. Read the CI/CD for ML guide above ⬆️

2. Build a GitHub Actions workflow that runs lint, tests, and data validation on every PR (the guide shows the pattern)