What is machine learning pipelines?

Machine learning pipelines are automated workflows that streamline the process of building, deploying, and managing machine learning models. They typically involve several sequential steps, including data ingestion, data preprocessing (cleaning, transformation, feature engineering), model training, model validation/evaluation, model deployment, and monitoring. These pipelines enable faster iteration, reproducibility, and scalability in machine learning projects by automating repetitive tasks and ensuring consistent model performance.