Understanding MLOps
Machine Learning Operations (MLOps) is a practice that blends the fields of ML and system operations. It is designed to standardize and streamline the life cycle of ML model development and deployment, thus increasing the efficiency and effectiveness of ML solutions within a business setting. In many ways, MLOps can be considered a response to the challenges associated with operationalizing ML, bringing DevOps principles into the ML world.
MLOps aims to bring together data scientists, who typically focus on model creation, experimentation, and evaluation, and operations professionals, who deal with deployment, monitoring, and maintenance. The goal is to facilitate better collaboration between these groups, leading to faster, more robust model deployment.
The importance of MLOps is underscored by the unique challenges presented by ML systems. Machine learning systems are more dynamic and less predictable than traditional software systems, leading to potential...
