Basics of End-to-End MLOps

Name: Basics%20of%20End-to-End%20MLOps
Uploaded: 2021-10-20T08:00:00.000Z

Posted Oct 20, 2021 | Views 708

Raviraja Ganta

Founding Engineer - NLP @ Enterpret

Raviraja is currently working at Enterpret as a Founding Engineer - NLP.

His interests are in Unsupervised Algorithms, Semantic Similarity, and Productionising the NLP models. Raviraja likes to follow the latest research works happening in the NLP domain.

Besides work, Raviraja likes cooking 🥘 , cycling 🚴‍♀️ , and kdramas 🎥.

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SUMMARY

MLOps, or DevOps for machine learning, enables data science and IT teams to collaborate and increase the pace of model development and deployment by monitoring, validation, and governance of machine learning models. To understand MLOps, we must first understand the ML systems lifecycle from developing ML models to deploying and monitoring them.

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Basics of End-to-End MLOps

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