Handling Imbalanced Dataset in Machine Learning: Easy Explanation for Data Science Interviews

Imbalanced Data is one of the most common machine learning problems you’ll come across in data science interviews. In this video, I cover what an imbalanced dataset is, what disadvantages it presents, and how to deal with imbalanced data when data contains only 1% of the minority class.

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Contents of this video:
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00:00 Introduction
01:20 Interview Questions
01:38 Imbalanced Data
03:15 Why it causes problems?
04:27 How to deal with imbalanced data?
08:13 Model-level methods
11:33 Evaluation Metrics
13:25 Outro