Class imbalance: How to deal with imbalanced data in Machine Learning

When observation in one class is higher than the observation in other classes then there exists a class imbalance. Example: To detect fraudulent credit card transactions. As you can see in the below graph fraudulent transaction is around 400 when compared with non-fraudulent transaction around 90000. Class Imbalance is a common problem in machine learning, especially in classification problems. Imbalance data can hamper our model accuracy big time.