Machine Learning Approaches for Improvising Modern Learning Systems

Zameer Gulzar

ISBN 10: 1799851532 / ISBN 13: 9781799851530

Verlag: Information Science Reference, 2021

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - 'This book explores the theoretical and practical aspects of technological enhancements in educational environments and the popularization of contemporary learning methods in developing countries'.

Bestandsnummer des Verkäufers 9781799851530

Bibliografische Details

• Titel: Machine Learning Approaches for Improvising Modern Learning Systems
• Verlag: Information Science Reference
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 1799851532
• ISBN-13: 9781799851530
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 254B x 178 H x 19 T Millimeter Breite: 254 mm, Höhe: 178 mm, Tiefe: 19 mm
• Gewicht: 677 Gramm

Über diesen Titel

Inhaltsangabe

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.

Über die Autorin bzw. den Autor

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.