Machine learning algorithms for predicting the graduation admission
With the rise in the number of graduates wishing to continue their education, it has become more difficult for students to gain admission to their desired university. Typically, newly graduated students are unaware of the standards and procedures for postgraduate admission and may spend a significant amount of money seeking guidance from consulting firms to help them determine their prospects of admission. However, given the restricted number of colleges that a human consultant can assess, this technique may be biased and erroneous. Higher education at foreign universities often implies that we have a wide range of possibilities, such as Canada, the United States, the United Kingdom, Germany, Italy, and Australia. However, we are only interested in students who wish to pursue their master’s degree in America. Students who desire to pursue a master’s degree in America must take the GRE (Graduate Records Examination) and the TOEFL (Test of English as a Foreign Language) (Test of English as a Foreign Language). They must compose their SOP (statement of purpose) and LOR (letter of reference) after they have completed the tests, which is one of the most important elements they must consider. These letters of recommendation and statements of purpose are crucial if the student is applying for a scholarship. When it comes to applying to master’s programmers, prospective graduate students are constantly faced with a conundrum when picking which universities to attend. While many predictors and consultancies can help a student, they aren’t always accurate because admissions decisions are based on a small number of historical admissions. As a result, with the rising demand for higher education, one should not be confused about where to apply. The pupils must next choose which institutions they wish to attend or apply to; we cannot apply to all universities because that would result in a large number of application fees. Here’s the issue: the student has no idea which university he might be accepted to. Several internet blogs can help with these issues, but they aren’t always correct and don’t take all of the elements into account, and some consulting firms will take a lot of our money and time while occasionally providing inaccurate information. As a result, our goal is to create a model that would tell students their chances of being accepted into a specific university. This model should take into account all of the important aspects that play a role in the student admissions process and should be highly accurate.