/Marks-Predictor

# Score-Predictor A simple project which predicts student's score in exam. Linear Regression is used to train the model. Label encoding is also done to encode categorical data. 32 Features are used to predict marks. The data set is taken from UCI Machine Learning Repository. Flask is used to integrate the machine learning model with the webpage. The root mean square error is 1.19.

Primary LanguageJavaScript

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