Introduction to Data Governance for Machine Learning Systems: Fundamental Principles, Critical Practices, and Future Trends

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024

A. Nandan PrasadIntroduction to Data Governance for Machine Learning Systemshttps://doi.org/10.1007/979-8-8688-1023-7_3

3. Data Quality and Preprocessing

Aditya Nandan Prasad¹  

(1)

Bangalore, Karnataka, India

 

In the fast-paced world of machine learning, data truly is king. While complex algorithms can uncover patterns, make predictions, and even automate processes, their success hinges on one crucial element: the quality of the data they’re fed. This chapter kicks off by diving into the essential role that data quality and preprocessing play in building reliable and accurate machine learning models. It makes a clear point that the effectiveness of these models ...