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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM20136

Career Prediction System

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM20136

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AH

Aayusha Hadke

GM

Gaurishankar Mali

SM

Shruti Mahale

SP

Swarup Pawar

PG

Prof.Rama Gaikwad

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Abstract

Machine learning algorithms have recently demonstrated considerable potential in predic ing career pathways based on unique qualities and traits. In this study, we offer a career prediction system that examines an individual’s qualities and characteristics, such as their school level, work ex perixence, and skills, using machine learning algorithms. To train the machine learning algorithms, we employed a dataset of individuals from various backgrounds and sectors. The system predicts a per- son’s career path using a variety of methods .The accuracy of these algorithms has also been examined in order to identify which one yields the greatest outcomes. Career Expectation Framework could be a web-based application that makes a difference clients to decide the foremost appropriate career way for them based on their abilities, interface, and identity characteristics. This framework employments machine learning calculations to analyze client infor- mation and give personalized career proposals. In this paper, we show a point by point portrayal of the framework engineering, the machine learning calculations utilized, and the assessment comes about.

KEYWORDS

Machine Learning Algorithm Random Forest Binary Classification Logistic Function Sigmoid Function Maximum Likelihood Estimation Decision Boundary Cost Function

Cite This Article

Aayusha Hadke, Gaurishankar Mali, Shruti Mahale, Swarup Pawar, Prof.Rama Gaikwad, "Career Prediction System," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023. https://doi.org/10.55041/IJSREM20136

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Publication Date

3/5/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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