Experiment tracking is the process of recording all the important components such as hyper parameters, metrics, models and artifacts like plots PNG images, files etc. Experiment tracking helps to reproduce the old results by using the stored parameters.
MLOps: A Complete Guide to Machine Learning Operations | MLOps vs DevOps
MLOps is the union of DevOps, machine learning, and data engineering. Built on DevOps’ existing approach, MLOps solutions are developed to increase re-usability, facilitate automation, manage data drift, model versioning, experiment tracking, continuous training and extract richer and consistent insights in a machine learning project.