Abstract: This study uses deep learning techniques to predict the academic performance of postgraduate (PG) students. By analyzing data such as grades, attendance, and online activity, we trained models like Deep Neural Networks (DNN) and Recurrent Neural Networks (RNN). Results show DNN achieving approximately 89% accuracy, making it an effective tool for early intervention.
Keywords: Deep Learning, DNN, RNN, Data Mining.
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DOI:
10.17148/IJARCCE.2025.14464
How to Cite:
[1] Ms. Neeta Takawale, Mrs. Asmita Kurhade, "Analyzing PG Student Performance Using Deep Learning," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14464
