MLOps is defined as set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently.
The aim is to create production level pipeline that promotes automation while making it transparent to help debugging.
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Currently if you search there are numerous tools available to implement ML production. Just as DevOps some of them merely differ in the choice of frameworks while others differ entirely in the concept.
This page is meant to be a toolshed for all these tools, where all different methods and tools are kept and labeled.
We will try to be as exhaustive as possible. Please reach out if some of the tools are not mentioned or misrepresented.