Recommendation Engine

Many students fail to meet academic standards due to outdated teaching methods. This harms them and society in various ways. A personalized learning recommender system using deep neural networks can help students learn better and overcome challenges. This system will tailor learning to each student’s needs and preferences, and improve education quality and equity.

The project provided valuable and precise recommendations to students, aiming to enhance their quiz performance. Leveraging neural collaborative filtering, an advanced recommendation algorithm widely used in recommender systems, the project focused on delivering tailored suggestions to students. The ultimate goal was to encourage student engagement with these recommendations, thereby contributing to overall performance improvement in quizzes.