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Machine Learning Approaches for Improvising Modern Learning Systems
Gulzar, Zameer ; Leema, A. Anny (Author)
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Information Science Reference
· Hardcover
Machine Learning Approaches for Improvising Modern Learning Systems - Gulzar, Zameer ; Leema, A. Anny
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Origin: U.S.A.
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Synopsis "Machine Learning Approaches for Improvising Modern Learning Systems"
Technology is currently playing a vital role in revolutionizing education systems and progressing academia into the digital age. Technological methods including data mining and machine learning are assisting with the discovery of new techniques for improving learning environments in regions across the world. As the educational landscape continues to rapidly transform, researchers and administrators need to stay up to date on the latest advancements in order to elevate the quality of teaching in their specific institutions. Machine Learning Approaches for Improvising Modern Learning Systems provides emerging research exploring the theoretical and practical aspects of technological enhancements in educational environments and the popularization of contemporary learning methods in developing countries. Featuring coverage on a broad range of topics such as game-based learning, intelligent tutoring systems, and course modelling, this book is ideally designed for researchers, scholars, administrators, policymakers, students, practitioners, and educators seeking current research on the digital transformation of educational institutions.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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