Machine Learning Approaches for Improvising Modern Learning Systems - Couverture souple

Couverture souple

ISBN 10 : 1799851532 ISBN 13 : 9781799851530

Editeur : Business Science Reference, 2021

Synopsis

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.

A propos du livre

À propos de l?auteur

Zameer Gulzar is an Assistant Professor in the Department of Computer Application, BSAR Crescent Institute of Science and Technology, Chennai. The editor’s areas of interest are e-learning, ontology, recommender systems, multimedia. Semantic Web, etc.

Détails de l'édition

• Éditeur: Business Science Reference
• Date d'édition: 2021
• Langue: anglais
• ISBN 10: 1799851532
• ISBN 13: 9781799851530
• Reliure: Broché
• Nombre de pages: 336
• Éditeur: Gulzar Zameer, Leema A. Anny
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible