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PROJECT TOPIC: PREDICTING STUDENTS ACADEMIC PERFORMANCE USING ARTIFICIAL NEURAL NETWORK
Department: Computer Education
AMOUNT: 10,000
FORMAT: MS WORD
PAGES: 75
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Abstract Preview
In academics, performance prediction is relevant to student classification. Precise predictions in advance are of high concern for educational institutions. Conventional techniques of classifying students may not be efficient. However, using computing techniques may be helpful. Artificial Neural network is employed to complete the performance prediction procedure over MATLAB simulation tool. Efficiency of Neural Network is evaluated by its accuracy and Mean Square Error (MSE). This tool- Feed Forward Neural Network- with nine neurons in the hidden layer can be used for differentiating between students with high rate of success and at-risk students who are more liable to have low performance.
Keywords: Prediction, Artificial Neural Network, Perceptron Algorithm
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