MLOps for Beginners: Getting Started With MLOps

Machine learning (ML) has revolutionized various industries by enabling data-driven decision-making along with the automation of certain tasks. For instance, many banking institutions deploy advanced machine-learning models to detect fraudulent transactions. These models need to evolve constantly otherwise there will be a steep rise in false positives.

However, deploying new machine learning models in production can be challenging. Training the model on production data, deploying it, and maintaining it isn’t easy. Many a time, machine learning models in production fail to adapt to the changing data and environment. And doing all of it manually isn’t efficient.