This workshop introduces Docker and explains the motivation for containerized environments in Data Science. You will first learn what Docker is, and how it differs from traditional virtual machine-based approaches. Then, we will go through hands-on examples, such as creating and running a custom Docker image, spinning up a Jupyter image, and deploying a model to production.
In order to follow along with the hands-on examples, please make sure to install Docker Desktop before the workshop. The link can be found here: https://www.docker.com/get-started
Slides: https://bit.ly/3ms7ThS
