Q. What is the primary goal of dimensionality reduction techniques like Principal Component Analysis (PCA) in machine learning?

• (A) To increase model interpretability
• (B) To reduce the size of the training dataset
• (C) To perform unsupervised learning
• (D) To visualize data relationships