Use Imblearn (Imbalanced-Learn) to Handle Imbalanced Datasets

Imbalanced datasets are difficult to work with and hard to get good machine learning performance because of the unequal amount of information ML model can learn from all classes. In this video, we go through how to use the Imbalanced Learn library to resample the data and improve model performance. We'll also look at how to cross-validate in such a situation.

Code: https://github.com/avenir-tech/ml_modeling/blob/master/imblearn.ipynb

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