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1. Scalable Architecture for Automating Machine Learning Model Monitoring
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Last years, due to the advent of more sophisticated tools for exploratory data analysis, data management, Machine Learning (ML) model training and model serving into production, the concept of MLOps has gained more popularity. As an effort to bring DevOps processes to the ML lifecycle, MLOps aims at more automation in the execution of diverse and repetitive tasks along the cycle and at smoother interoperability between teams and tools involved. READ MORE
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