MLOps Is Changing How Machine Learning Models Are Developed - KDnuggets

MLOps refers to machine learning operations. It is a practice that aims to make machine learning in production efficient and seamless. While the term MLOps is relatively nascent, it draws comparisons to DevOps in that it's not a single piece of technology but rather a shared understanding of how to do things the right way. The shared principles MLOps introduces encourage data scientists to think of machine learning not as individual scientific experiments but as a continuous process to develop, launch, and maintain machine learning capabilities for real-world use. Machine learning should be collaborative, reproducible, continuous, and tested. The practical implementation of MLOps involves both adopting certain best practices and setting up an infrastructure that supports these best practices.