How to create a Docker data science container for Jupyter notebooks

Published on 31 October 2019

Introduction

What is perhaps the best way to run Jupyter notebooks on your local machine and in the cloud? Probably running your notebooks inside a Docker container. This ensures that your notebooks will run smoothly regardless of the OS or configuration of the host machine. And it makes installing and configuring Jupyter notebooks a breeze.

Key takeaways

  • Using Docker to create a data science container has many advantages over installing Jupyter directly on your machine.
  • Configure your data science Docker image in a Dockerfile.
  • Use docker build to create an image and run your image using docker run.
  • Run your image using docker run.
  • Don't forget create a Docker volume as a persistent storage option for your notebooks

References and resources

Academy Instructor

Nicolas Lierman

Chief Data Engineer

Nicolas is the Chief Data Engineer at MultiMinds. He has over 16 years of experience in marketing and online data. He's also an instructor at the training academy and teaches at the university.

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