Machine Learning base Student Future Orientation and Recommendation System

As students are rummaging their academics and pursuing their interested courses, they need to assess their capabilities and identify their interests in understanding during which career area their interests and abilities will put them in. With the rise in the number of career paths and opportunities, making this decision has become quite tricky for scholars. In keeping with the survey conducted by the Council of Scientific and Industrial Research (CSIR), about 40% of scholars are confused about their career options. This could result in wrong career selection, so working in a field that wasn't meant for them reduces human resource productivity. This project proposes feasible predictions for students' field selection supported by their marks and selection of interest. The system would recommend the scholar a career option that helped their personality trait, interest, and capacity to require up the course. This technique provides students with many career options per their part, self-talent, memorizing power, and most vital per their academic credit score. This technique generates a credit score supported by new government educational policies, helping students settle on correct streams for the longer-term career path.

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Machine Learning base Student Future Orientation and Recommendation System

Semantic Scholar · Computer Science · 2021

Abstract

As students are rummaging their academics and pursuing their interested courses, they need to assess their capabilities and identify their interests in understanding during which career area their interests and abilities will put them in. With the rise in the number of career paths and opportunities, making this decision has become quite tricky for scholars. In keeping with the survey conducted by the Council of Scientific and Industrial Research (CSIR), about 40% of scholars are confused about their career options. This could result in wrong career selection, so working in a field that wasn't meant for them reduces human resource productivity. This project proposes feasible predictions for students' field selection supported by their marks and selection of interest. The system would recommend the scholar a career option that helped their personality trait, interest, and capacity to require up the course. This technique provides students with many career options per their part, self-talent, memorizing power, and most vital per their academic credit score. This technique generates a credit score supported by new government educational policies, helping students settle on correct streams for the longer-term career path.

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