Unlocking Student Insights: Performance Analysis with Enhanced K-Means - Couverture souple

Sonawane, Ajay

9786208172374: Unlocking Student Insights: Performance Analysis with Enhanced K-Means

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ISBN 10 : 6208172373 ISBN 13 : 9786208172374

Editeur : LAP LAMBERT Academic Publishing, 2024

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Machine Learning (ML) is a branch of artificial intelligence that allows computers to learn from data without explicit programming. ML is applied in various fields, including education, pattern recognition, industries, social media, and product recommendations. In education, ML and Educational Data Mining (EDM) are becoming crucial due to the growing amount of student data. EDM helps uncover hidden information in educational datasets, aiding in student performance improvement and better decision-making for teachers and institutions. Techniques like clustering (e.g., modified K-means) and classification (e.g., decision trees) are commonly used to analyze student performance. Clustering groups students based on characteristics, while the Elbow method helps determine optimal cluster size. ML in education helps enhance student outcomes and optimize administrative decisions, making it valuable for both students and institutions. This data-driven approach is key to improving education quality in the future.

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2024
Langue: anglais
ISBN 10: 6208172373
ISBN 13: 9786208172374
Reliure: Broch�
Nombre de pages: 84
Coordonn�es du fabricant: non disponible
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Unlocking Student Insights: Performance Analysis with Enhanced K-Means

Sonawane, Ajay

Edit� par LAP LAMBERT Academic Publishing, 2024

ISBN 10 : 6208172373 ISBN 13 : 9786208172374

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Unlocking Student Insights

Sonawane, Ajay

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Unlocking Student Insights: Performance Analysis with Enhanced K-Means

Sonawane, Ajay

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Unlocking Student Insights: Performance Analysis with Enhanced K-Means

Ajay Sonawane

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Unlocking Student Insights: Performance Analysis with Enhanced K-Means

Ajay Sonawane

Edit� par LAP LAMBERT Academic Publishing, 2024

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine Learning (ML) is a branch of artificial intelligence that allows computers to learn from data without explicit programming. ML is applied in various fields, including education, pattern recognition, industries, social media, and product recommendations. In education, ML and Educational Data Mining (EDM) are becoming crucial due to the growing amount of student data. EDM helps uncover hidden information in educational datasets, aiding in student performance improvement and better decision-making for teachers and institutions. Techniques like clustering (e.g., modified K-means) and classification (e.g., decision trees) are commonly used to analyze student performance. Clustering groups students based on characteristics, while the Elbow method helps determine optimal cluster size. ML in education helps enhance student outcomes and optimize administrative decisions, making it valuable for both students and institutions. This data-driven approach is key to improving education quality in the future. N� de r�f. du vendeur 9786208172374

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Unlocking Student Insights: Performance Analysis with Enhanced K-Means

Ajay Sonawane

Edit� par LAP LAMBERT Academic Publishing Okt 2024, 2024

ISBN 10 : 6208172373 ISBN 13 : 9786208172374

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Taschenbuch. Etat : Neu. Neuware -Machine Learning (ML) is a branch of artificial intelligence that allows computers to learn from data without explicit programming. ML is applied in various fields, including education, pattern recognition, industries, social media, and product recommendations. In education, ML and Educational Data Mining (EDM) are becoming crucial due to the growing amount of student data. EDM helps uncover hidden information in educational datasets, aiding in student performance improvement and better decision-making for teachers and institutions. Techniques like clustering (e.g., modified K-means) and classification (e.g., decision trees) are commonly used to analyze student performance. Clustering groups students based on characteristics, while the Elbow method helps determine optimal cluster size. ML in education helps enhance student outcomes and optimize administrative decisions, making it valuable for both students and institutions. This data-driven approach is key to improving education quality in the future.Books on Demand GmbH, �berseering 33, 22297 Hamburg 84 pp. Englisch. N� de r�f. du vendeur 9786208172374

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