Personalized Analytics and Cognitive Evalution (PACE) using ElasticNet model.

#Using this web application , Professors , Students and Parents can predict the Semester exam marks.

#They can find it for each Semester using it's internal marks or the final semester using the previous 7 semester marks.

#Here ElasticNet model is used because it using regularization to solve underfitting and overfitting which gives accurate prediction

#Steps to run the software

1)Clone this repository

2)Connect your database which is used for login and history purposes.

3)Run the front-end folder usng command "npm start"

4)Run the python modules in the back-end folder.