Using BQML for feature transformations

Two types of feature preprocessing are supported by BQML:

• Automatic preprocessing: During training, BQML carries out automatic preprocessing. For further details, please carries out automatic preprocessing like missing data imputation, one-hot encoding, and timestamp transformation and encoding.
• Manual preprocessing: You can use the TRANSFORM clause provided by BQML to define customized preprocessing using manual preprocessing functions. These functions can also be utilized outside the TRANSFORM clause.

While BQML does support some feature engineering tasks, it has certain limitations compared to more flexible and feature-rich ML frameworks:

• Limited preprocessing functions: BQML provides a basic set of SQL functions for data preprocessing, such as scaling and encoding. However, it may lack some advanced preprocessing techniques or specialized functions available in other ML libraries such as scikit-learn or TensorFlow...