Why Is Mlops Important And What Are The Benifits Of The Mlops?

By Author: thoughtwareanalytics
Total Articles: 1
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Mlops is the process of combining the end to end process of design, develop, test and delivering of machine learning models in a single step. Mlops is just inheriting the good parts of devops into the ml space. In Software space only the code matters whereas in ML both the code and data matter.
benifits of mlops

* When there are many different teams working in an organization like data engineering team, ml dev team and operations team there is a bottleneck when the work of one team does'nt work good with the other teams code.

This can be done by using version control and the next version is approved only when the end to end pipeline is tested to work.

* With the pipeline approach the the updates performed by each of the team can be cross checked before pushing their changes.

* Machine learning come under tight scrutinity for explainability because humans do not explicitly specify any learning logic into the models thus it is essential to specify how the models was trained and how the data was collected.

* MLops also helps with domain shift problems as models can be trained, data collection all can be done on the fly.