Machine Learning Operations (MLOps): Standardizing Model Deployment and Monitoring to Avoid Model Drift in Production
Setting an ML model is only half the job; the other half—ensuring that it is deployed reliably, keeping a close watch on its behaviour, and maintaining its accuracy over time—is something that many teams find difficult. A model which performs well in a controlled testing environment can quickly fail to remain effective when it is … Read more