Mastering Feature Preprocessing in BigQuery ML

Discusses the new feature preprocessing capabilities of BigQuery ML, a tool for data analytics and machine learning that is part of Google Cloud’s BigQuery. The author explains that BigQuery ML enables data analysts and scientists to create and deploy machine learning models using SQL queries within the BigQuery environment. The article then provides a detailed overview of the new preprocessing features, including ML.IMPUTER for handling missing data, ML.LABEL_ENCODER for transforming categorical data, and ML.MAX_ABS_SCALER and ML.ROBUST_SCALER for scaling and normalizing data. The article concludes with a practical tutorial showing how to use these preprocessing features in a Python code example. Hosted on Acast. See acast.com/privacy for more information.