Docker for Data Science

If you're not familiar with Docker, you should spend some time with it. 

Think of Docker as a light virtual machine . Someone writes a Dockerfile that builds a Docker Image which contains most of the tools and libraries that you need for a project. You can use this as a base and add any other dependencies that are required for your project. Its underlying philosophy is that if it works on my machine it will work on yours.

I picked up Docker basics in a day a couple of years ago and have found it to be a very useful tool in my kit. This article is good jumping-off point.


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