What is ML Pipelines?

ML Pipelines automate the process of training, evaluating, and deploying machine learning models. They consist of a sequence of interconnected steps, such as data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment. ML pipelines ensure reproducibility, scalability, and efficiency in ML workflows, allowing for easier management and monitoring of models in production. They are commonly used to streamline and automate the entire ML lifecycle.