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Student Performance Prediction

Developed a machine learning model to predict Student performance in exam using a dataset of student performance. Preprocessed data performed feature engineering and applied gridsearchcv to find the best model as Linear Regression with the accuracy of 87%. Created a Flask app for users to predict the student performance using frontend. Technologies Used: Python scikit-learn pandas Matplotlib Flask.

💻 Built with

Technologies used in the project:

  • Python
  • Pandas
  • Numpy
  • Seaborn
  • Maplotlib
  • Scikit-Learn
  • Flask

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