Название: Artificial Intelligence Theory, Models, and ApplicationsАвтор: P. Kaliraj, T. Devi
Издательство: CRC Press/Auerbach Publications
Год: 2022
Страниц: 507
Язык: английский
Формат: pdf (true)
Размер: 29.4 MB
This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills.
The Chapter 14 introduces Machine Learning (ML) in a simple way to novices in the area. It gives the reader an understanding of the importance of Machine Learning and the steps involved in making a machine learn. The chapter also provides an overall picture of the various forms of Machine Learning and the several algorithms that make machines behave like smart machines. It also deals with some problem areas where ML could be successfully used and introduces the various tools (Tensor Flow, PyTorch, Spark ML Library, Scikit-learn, Amazon Machine Learning) available for ML today. This chapter ends with a description of the various application areas where machine learning is used.
Features:
Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world
A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization
The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine
AI’s role in the diagnosis of various diseases, such as cancer and diabetes
The role of Machine Learning (ML) models in product development and statistically monitoring product quality
Machine Learning to make robust and effective economic policy decisions
Machine Learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results
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