Description
This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.
Table of Contents
Introduction.- Model-Centric AI.- Data-Centric Principles for AI Engineering.- Mathematical Foundation for Data Centric AI.- Data-Centric AI.- Data-Centric AI in healthcare.- Data-Centric AI in Mechanical Engineering.- Data-Centric AI in Information Communication and Technology.- Conclusion.
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