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Education Data Mining is vividly advancing in the field of research due to the increasing amount of data on a daily basis. EDM deals with extracting meaningful information from the education setting. To analyse and understand the ever-growing education data, Machine learning algorithms are employed to classify and cluster the datasets. Research in this field focuses on understanding the behaviour analysis of students, classifying the students to predict the academic outcome, clustering the students based on various factors that can influence the performance and many more. Many researchers have…mehr

Produktbeschreibung
Education Data Mining is vividly advancing in the field of research due to the increasing amount of data on a daily basis. EDM deals with extracting meaningful information from the education setting. To analyse and understand the ever-growing education data, Machine learning algorithms are employed to classify and cluster the datasets. Research in this field focuses on understanding the behaviour analysis of students, classifying the students to predict the academic outcome, clustering the students based on various factors that can influence the performance and many more. Many researchers have recommended a recommender system to achieve the goal of identifying and classifying the students based on their performance.
Autorenporträt
Sujith Jayaprakash est un professionnel du développement commercial très motivé, qui possède une solide expérience de la formation et de l'administration dans le domaine des technologies de l'information. Il a plus de dix ans d'expérience dans les secteurs de l'éducation en Inde, en Afrique et en Amérique latine, avec une expérience significative dans des rôles de cadres supérieurs et dans l'amélioration de l'enseignement institutionnel.