Explain the concept of Spark’s ML Pipelines.

Spark’s ML Pipelines provide a high-level API for building and deploying machine learning workflows. The pipelines consist of a sequence of stages, including transformers, estimators, and model selectors. Transformers transform input data, estimators fit models to the data, and model selectors automatically choose the best model based on evaluation metrics. The pipelines simplify the process of building end-to-end machine learning workflows and enable easy experimentation and model deployment at scale.