Unboxing the Concept of Drift in Machine Learning - Symbl.ai

Machine Learning Drift is a common phenomenon that occurs once the machine learning algorithm is deployed to production. It can adversely affect the overall performance of your machine learning model if not monitored closely and mitigated at the right time. This article will provide an overview of machine learning drift and various types of drift, as well as cover some practical techniques to eliminate drift. Machine learning and AI models are built on the assumption that historical data projects an accurate representation of the future. But in a fast-changing world, this is rarely the case.