Using Deep Learning to Predict Scholarship Scheme Based on Student Details

Abstract

The government launches various ambitious programs to make the country more prosperous, but they fail in successful implementation. The main reason behind this issue is the lack of awareness among rural people. This project is to provide a solution to this unaware situation. Through this system, rural students will get to know about what are the various schemes that are furnished by the government. Initially, this system will explore government schemes that are available for the welfare of rural students. Next, the student's datset ((i.e.) name, age, caste, occupation, annual income, etc.) are collected. Then both the datasets are imported into the Anaconda Navigator. Later analysis and classification are done based on communities (SC, ST, BC MBC, and DNC), Educational category (Pre-metric/Post-metric), Board of education (Government/Government-aided), Day scholar or hosteller, age of the students and the schemes are predicted.