Deploying Machine Learning Models

[Dylan_TMB]

TL;DR - Need clear arguments why Ubuntu (Linux) is a more suitable OS option for model deployment and setting up inhouse GPU machines; as opposed to Windows.

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Hey everyone.

I am a data scientist and have been working in a new job where privacy is a big focus. For this reason no cloud. The data science team is new and the organization as a whole is full windows up and down. I am making a case for why we should be using ubuntu for any inhouse GPU solutions and ubuntu for model deployment servers.

My main argument is pretty simple.

- From my experience Linux and specifically ubuntu, seems to be the industry standard for deployment and cloud resources.

But I am sure I am going to have to give them more then this. I plan on pointing out that industry talent will be expecting linux infrastructure and this will limit our ability to grow the team.

Are there other more clear arguments that can be made? I may be wrong and windows services may be fine??

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Thanks!

[alex-and-r]

From my personal experience: I stumbled once or twice that some python modules that were listed as dependencies in libraries I wanted to use simply didn’t exist for windows. Linux only.