Predicting Student Performance Using Personalized Analytics PROJECT TITLE :Predicting Student Performance Using Personalized AnalyticsABSTRACT:To assist solve the continued downside of student retention, new expected performance-prediction techniques are required to facilitate degree coming up with and confirm who would possibly be in danger of failing or dropping a class. Personalized multiregression and matrix factorization approaches based mostly on recommender systems, initially developed for e-commerce applications, accurately forecast students' grades in future courses and on in-category assessments. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Facilitating Creativity in Collaborative Work with Computational Intelligence Software Spectral–Spatial Sparse Subspace Clustering for Hyperspectral Remote Sensing Images