data cleaning

Data typically needs some “cleaning” prior to being used in machine learning models. For example, an unusually large number may represent a data entry error, or it could be an outlier that’s unusual but correct. Clean data is essential to high-quality machine learning models. also known as data cleansing, data preprocessing