How to use SMOTE for dealing with imbalanced image dataset for solving classification problems

Deep Learning Algorithms are often considered to be magical black boxes that can solve any problem which you throw at them. But how true is this statement? Well, it might be true in some cases but unfortunately the “magic” vanishes when you are trying to solve a classification problem with these algorithms but all you have is a highly skewed and imbalanced dataset! In case if you want to follow other works of mine, please visit my website.

Not sure of what we are talking about? Let’s take an example, to understand the problem better and then discuss about how it can be solved and how SMOTE is a very powerful and effective approach to tackle such problems.

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