Summary  
This chapter explains how to construct a grid of hyperparameter combinations using ParamGridBuilder and apply systematic search (e.g., grid search with cross-validation) to find optimal model settings.  

General domain of usage  
Machine learning

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.

Hyperparameter Tuning with ParamGridBuilder