It is common to come across an imbalanced dataset while working on classification problems such fraud detection, spam detection, or mapping natural resource occurrences. An imbalanced dataset is one that contains unequal number of samples from each class. This notebook will walk you through the steps for dealing with an imbalanced dataset using an example of a real project that I recently completed.