Review on “COLLEGE RECOMMENDATION SYSTEM FOR STUDENT”

Review on “COLLEGE RECOMMENDATION SYSTEM FOR STUDENT”

Prof. Pooja More

Professor

Department of Computer Engineering, GHRIET

Pune, India

Prathamesh Rajgure

Student

Department of Information Technology, GHRIET

Pune, India
Saurabh Saraf

Student

Department of Information Technology, GHRIET

Pune, India

Aadesh Jaiswal

Student

Department of Information Technology, GHRIET

Pune, India
 

Abstract

In this paper, we propose a college recommendation system that uses machine learning algorithms to help high school students choose the best college for their needs and preferences. The system takes into account various factors such as academic performance, extracurricular activities, financial aid, location, and program offerings to provide personalized college recommendations to each student. The system is designed to be user-friendly and accessible, with a simple interface that allows students to input their information and preferences easily. The system uses a variety of machine learning algorithms, including collaborative filtering and content-based filtering, to analyze the data and provide accurate and personalized recommendations. The proposed college recommendation system has several advantages over traditional methods of college selection, including its ability to consider

a wide range of factors and provide personalized recommendations based on individual needs and preferences.

Keywords: College selection, Machine learning algorithms, Personalized recommendations, User-friendly interface, Academic performance.