Summary  
This chapter covers methods for ingesting datasets from various sources, cleaning and transforming the data, and partitioning it into training and test sets to prepare for modeling.  

General domain of usage  
Machine learning pipelines

Master machine learning techniques using PySpark and real estate data. Learn to build, evaluate, and optimize ML pipelines for classification, regression, and clustering tasks using Spark MLlib.

Comprehensive guide to machine learning with PySpark using real estate data, covering classification, regression, clustering, and pipeline optimization.

Loading and Preparing Data for ML