A Quantitative and Qualitative Approach To Data Cleaning

Author(s): Kaushik Choudhury

Originally published on Towards AI.

Clean data is the oxygen that enables the trained machine learning models to deliver Olympic-level performance.

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Photo by Lina Verovaya on Unsplash

When we started learning COBOL in high school, one of the first things the teacher introduced was the concept of GIGO. GIGO stands for “garbage in, garbage out”. If we input clutter mishmash data to a program, it will either error out or provide inaccurate results. This fundamental principle has not changed in machine learning programming. Moreover, it has become more relevant over time, considering the massive amount of data required to train a model for real-life artificial intelligence use cases.

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Published via Towards AI