Career Prediction System

Career Prediction System

Aayusha Hadke¹, Gaurishankar Mali², Shruti Mahale³, and Swarup Pawar⁴

Guided By Prof.Rama Gaikwad

ANANTRAO PAWAR COLLEGE OF ENGINEERING RESEARCH. S. No. 103, Shahu College

Road, Parvati,Pune - 411009

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

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.