Balanced Batch Generation for Imbalanced Datasets

In this project, you will learn how to implement an unbalanced data pipeline that can process imbalanced datasets and generate batches with approximately balanced class distributions. This is a common task in machine learning, where the dataset may have significantly more samples from one class compared to others, which can lead to biased model training and poor performance.