ML Data Processing

Effective machine learning relies on high-quality data processing techniques that transform raw information into meaningful input for algorithms. This chapter explores the core methods involved in preparing data for machine learning models, from data cleaning and normalization to feature engineering and dimensionality reduction. We’ll also cover the essential steps of splitting datasets into training, validation, and test sets to ensure unbiased model evaluation.

ML Data Processing

With these skills, you’ll be able to optimize data to enhance model performance, minimize errors, and streamline the overall machine learning workflow.