A short guide to using Docker for your data science environmentSay goodbye to OS troubles and hello to portability!NileshBlockedUnblockFollowFollowingDec 8WHYOne of the most time consuming part of starting your work on a new system/starting a new job or just plain sharing your work is the variation of tools available (or lack thereof) due to differences in hardware/software/security policies and what not..In this article we’ll go through Docker as our container service and steps needed to get started with building your custom development platform for data science.Personally, I believe that the ability to build upon other’s systems is one of the biggest advantages while using docker..You can clone a image using docker pull command :docker pull pythonApproach B : Use an already available image with all your tools installedThis is the reason I have fallen in love with using docker for my data to day work.. More details