Graduate University Admission Predictor using Machine Learning

With the increase in the number of graduates who wish to pursue their education, it has become morechallenging to get admission for the students in their dream university. Usually, newly graduate students arenot knowledgeable of the requirements and the procedures of the postgraduate admission and might spent aconsiderable amount of money to get advice from consultancy organisations to help them identify theiradmission chances. Giving the limited number of universities that can be considered by a human consultant,however, this approach might be bias and inaccurate. Higher education in abroad universities generallymeans we have many options like Canada, USA, UK Germany, Italy, Australia etc. But we are focusing ononly the students who want to do their Masters in America. Students who want to do masters in Americahave to write GRE (Graduate Records Examination) and TOEFL (Test of English as a Foreign Language). Oncethey have attended the exams they have to prepare their SOP (statement of purpose) and LOR(letter ofrecommendation) which are one of the crucial factors they have to consider. These LOR and SOP plays a vitalrole if the student was looking for any scholarship. Prospective graduate students always face a dilemmadeciding universities of their choice while applying to master's programs. While there are a good number ofpredictors and consultancies that guide a student, they aren't always reliable since decision is made on thebasis of select past admissions. So, with increasing demand of further education, one must not be confusedin where to apply. Then the students have to choose the universities they want to study or apply, we cannotapply to all the universities that will lead to lot of application fees. Here comes the problem that the studentdoesn’t know to which university he might get admission. There are some online blogs which help in thesematters but they are not that much accurate and don't consider all the factors and there are someconsultancy offices which will take lot of our money and time and sometimes they will give some falseinformation.so our goal is to develop a model which will tell the students their chance of admission into arespective university. This model should consider all the crucial factors which plays a vital role in studentadmission process and should have high accuracy.