Reproducible data science workflows using Docker

Want to eliminate the hassle of inconsistent programming environments and achieve reproducible data science? Watch this session to learn how Docker can help you achieve that and more! Learn the basics of Docker, including creating and running containers, working with images, automating image building using Dockerfile, and managing containers on your local machine and in production.

You will also see real-world examples of how other data scientists use Docker to streamline their workflow and address common challenges like reproducibility and dependency management.

This session is interactive and hands-on so that you can learn and apply the techniques yourself!