• Sharvari Salgaonkar
• Akshat Patel
• Parth Vaghela
• Sweedle Machado
• Sharvari Patil

The process of choosing the appropriate college and course based on the obtained score and making an informed decision can be intimidating, and students sometimes struggle to estimate which universities they will be admitted to. There are some existing projects that refer to this issue but they lack in encompassing all colleges present in Maharashtra and also, they do not provide the facility to choose a college which is distance friendly and saves traveling time. This research work proposes an Engineering admission recommendation system for helping students choose the best college and branch based on their preferences for the MHT-CET examination. The system takes as input the student’s percentile/rank and based upon college rankings, location, available branches, seats, and the previous year's cut-off to generate an ideal preference list and determine the chances of admission. The new dataset consisting all engineering colleges of Maharashtra has been created and Machine learning models such as Regression and other techniques are used to analyze the dataset and provide suitable output. This application aims to help students secure admission to their desired college in a hassle-free manner.

Admission Recommendation System, Prediction, Machine Learning Algorithms, MHT-CET, Preference List.

"College Predictor using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.o122-o128, April-2024, Available :http://www.jetir.org/papers/JETIR2404F17.pdf

"College Predictor using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppo122-o128, April-2024, Available at : http://www.jetir.org/papers/JETIR2404F17.pdf