GradHelp

Machine learning application made using React.js, FastAPI and MongoDB. Uses SVC to predict user's chance of admission in top US universities. Also a Keras neural network is used to recommend universities based on user profile.

Docker Images

Client Docker Image || Server Docker Image

MODULE 1: Homepage

Homepage of the application from where users can access other modules. Application is styled using TailwindCSS.

MODULE 2: User Profile

Users can create their profile which will be used by the ML models. The profile data is also stored in localstorage to persist between sessions.

MODULE 3: Admission Chance Prediction

Users can explore the top 300 US universities, which is retrieved from MongoDB. User's chance of admission is predicted using a Support Vector Classifier model.

MODULE 4: University Recommendations

Three universities are recommended to the users based on their profile. A Keras neural network is used to generate recommendations.