What are the most common data preprocessing techniques used in machine learning?
Data preprocessing is an essential step in machine learning that involves transforming raw data into a suitable format for analysis and modeling. Data preprocessing can improve the quality, accuracy, and efficiency of machine learning algorithms by reducing noise, errors, outliers, and missing values. In this article, you will learn about some of the most common data preprocessing techniques used in machine learning and how they can help you achieve better results.