Year: 2025
Type: article
Abstract: : Nowadays, one of the most important topics is admissions. Nowadays, everyone expects to be admitted to a university in their selected field or speciality, but a student's uncertainty about his chances of being accepted has long been a big admissions issue. Securing admission to prestigious colleges has become a significant problem for students globally in the current competitive academic climate. Universities evaluate applications using a variety of academic and non-academic criteria because there are thousands of applicants vying for a small number of places. Data-driven models can play a vital role in helping students understand their prospects of acceptance. . The goal of this project, "University Admission Chance Predictor," is to calculate the likelihood that a student will be accepted into a university by taking into account important admissions criteria. One of the biggest topics these days is poultry admissions. While getting into a university in one's selected field or speciality is something that everyone hopes to do, a student's odds of getting accepted are unknown, which has always been a big admissions concern. Using a variety of libraries, including pandas and numpy, the university admission probability predictor analyses student-provided data and makes predictions based on it. It also indicates whether or not you have a chance in your chosen subject, branch, or domain
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4416208659
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