Prediction Probability of Getting an Admission into University Using ML

In present conditions, student having difficulties in finding a satisfied institution to pursue higher studies based on their profile. There are some advisory administrations and online applications that recommend universities but they charge consultancy fees in huge amount and online apps are not accurate. So, the main aim of this research is to develop an accurate model that can predict the percentage of chances of getting an admission into the university accurately. This model also provides the analysis of scores versus chances of prediction based on historical data so that students can understand properly whether their profile is suitable for the particular institution or not. Linear Regression and random forest algorithms are uses in this model but cat boost algorithm give the highest accuracy.