Machine Learning for Predictions in Academics
Shashi Sharma1, Sunil Kumar Pandey2, Kumkum Garg3
1Shashi Sharma, School of Computing Skills, Bhartiya Skill Development University, Jaipur, India.
2Sunil Kumar Pandey, School of Computing Skills Bhartiya Skill Development University, Jaipur, India.
3Prof.(Dr.) Kumkum Garg, Dean Academics Bhartiya Skill Development University, Jaipur, India 

Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4624-4627 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6965018520/2020©BEIESP | DOI: 10.35940/ijrte.E6965.018520

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Abstract: In recent years, a lot of data has been generated about students, which can be utilized for deciding the career path of the student. This paper discusses some of the machine learning techniques which can be used to predict the performance of a student and help to decide his/her career path. Some of the key Machine Learning (ML) algorithms applied in our research work are Linear Regression, Logistics Regression, Support Vector machine, Naïve Bayes Classifier and K- means Clustering. The aim of this paper is to predict the student career path using Machine Learning algorithms. We compare the efficiencies of different ML classification algorithms on a real dataset obtained from University students.
Keywords: Machine Learning, Student Performance.
Scope of the Article: Machine Learning.