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With the increasing number of graduates seeking to pursue higher education, getting a student's admission into the university becomes more challenging. New graduate students are typically unaware of the postgraduate admission criteria and procedures and may spend a substantial amount of time obtaining guidance from consulting firms to help them define their admission opportunities. But this methodology can be biased and misleading considering the small number of universities that a human consultant may consider. Thus, a machine learning approach was built in this paper to automatically predict the prospects for postgraduate admissions, enabling graduates to recognise and target the most appropriate universities for their profile. The University Recommendation System for Higher Studies is a system framework that prescribes universities for students or users of the system who recommend universities to students looking for education for their higher studies. The main parameters used to recommend university are CGPA percentages, GRE Score, TOFEL Score, university rank, etc. This system uses machine learning algorithms and compares the accuracy of the algorithms.

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