Amazon SageMaker Data Wrangler is a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and combine features without having to write any code.
Today, we’re excited to announce new transformations that allow you to balance your datasets easily and effectively for ML model training. We demonstrate how these transformations work in this post.
New balancing operators
The newly announced balancing operators are grouped under the Balance data transform type in the ADD TRANFORM pane.

Currently, the transform operators support only binary classification problems. In binary classification problems, the classifier is tasked with classifying each sample to one of two classes. When the number of samples in the majority class (bigger) is considerably larger than the number of

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