Machine Learning Operations (MLOps): Overview, Definition, and Architecture

🤖 Plain-English Summary

The final goal of all industrial machine learning (ML) projects is to develop ML products and rapidly bring them into production. Additionally, we provide a comprehensive definition of MLOps and highlight open challenges in the field.

🔑 Key Findings

• However, it is highly challenging to automate and operationalize ML products and thus many ML endeavors fail to deliver on their expectations.
• The paradigm of Machine Learning Operations (MLOps) addresses this issue.
• MLOps includes several aspects, such as best practices, sets of concepts, and development culture.

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