Student Career Prediction Using Machine Learning
Umesh Kumar Sah
, Awantika Singh
Machine Learning Classifier, Support Vector Machine, Adaboost, Random Forest, Decision Tree.
There are number of good schools and colleges in India. But most of the students are dropping their education because of various reasons. There are many reasons, some of the students have some financial problem with their family, some of the students don’t have interest towards their next level of education, some student think about gender and some about rural areas don’t have good schools and educators. In today’s world choosing an appropriate career path is one of the most important decisions but with the increase in the number of career options and opportunities, it makes this decision even more difficult for the students. Different people suggest different career paths to the student but at last the student have to select their career themselves. According to the survey conducted by the Council of Scientific and Industrial Research’s (CSIR), about 40% of students are confused about their career selections. This may lead the students to wrong career selection and then working in an area which was not meant for them, this leads their career in wrong path, and this may not be good for their future career. Therefore, it is very important to take a right decision regarding the future career in right time. So this proposed method deals whether the students will be going to the next level of higher education or not. This can be decided with the concepts of machine learning which is the subset of artificial intelligence. Machine learning is made up with the concepts of Mathematics and Science. This paper deals with the student’s career prediction by using various machine learning algorithms like Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM) and Adaboost. Machine learning algoriths are implemented by using Python programming language.
"Student Career Prediction Using Machine Learning", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.343 - 347, May-2022, Available :https://ijsdr.org/papers/IJSDR2205065.pdf
Volume 7
Issue 5,
May-2022
Pages : 343 - 347
Paper Reg. ID: IJSDR_200320
Published Paper Id: IJSDR2205065
Downloads: 000347345
Research Area: Science & Technology
Country: Raipur, Chhattisgarh, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
