About this document
Data Preprocessing vs Feature Engineering by Mariamawit Nejib is a document available to read on EtoBox.
Chapter 5 discusses data preprocessing and feature engineering as essential steps in the machine learning pipeline, emphasizing the need to clean and prepare raw data for effective model training. It covers techniques for data cleaning, feature encoding, scaling, transformation, and dimensionality reduction, highlighting their importance in improving model performance and accuracy. The chapter also outlines various methods for feature selection and extraction to enhance model interpretability and reduce ove
- Author
- Mariamawit Nejib
- Language
- EN