Data-Centric Artificial Intelligence for Multidisciplinary Applications

By: Gitanjali R. Shinde (Editor), Parikshit N Mahalle (Editor), Namrata Nishant Wasatkar (Editor)

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Hardcover | 6 June 2024 | Edition Number 1

At a Glance

Hardcover
310 Pages

Dimensions(cm)
23.4 x 15.6 x 1.91

Hardcover

RRP $307.00

$265.75

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This book explores the need for a data-centric AI approach and its application in the multidisciplinary domain, compared to a model-centric approach. It examines the methodologies for data-centric approaches, the use of data-centric approaches in different domains, the need for edge AI and how it differs from cloud-based AI. It discussed the new category of AI technology, "data-centric AI" (DCAI), which focuses on comprehending, utilising, and reaching conclusions from data. By adding machine learning and big data analytics tools, data-centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods.

* Includes a collection of case studies with experimentation results to adhere to the practical approaches

* Examine challenges in dataset generation, synthetic datasets, analysis and prediction algorithms in stochastic ways

* Discusses methodologies to achieve accurate results by improving the quality of data

* Comprises cases in Healthcare and Agriculture with implementation, impact of quality data in building AI applications

* Addresses privacy and security challenges in Data-centric AI

The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.

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