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Title

People Thoughts Prediction using Machine Learning on Women's Contribution in ICT in Bangladesh

Author

Sharmin Akter, Israt Jahan, Mehnaz Rashid Mim, Sunzida Siddique, Tapasy Rabeya,

Email

Abstract

Now a days Women have become more career-conscious in the present eradication. They wish to pursue careers that were previously only available to men. Women's participation in the workforce has risen in Bangladesh day by day. The number of women working in the information technology industry is astounding. The purpose of this study is to predict people thinking of women in the IT sector as their career in Bangladesh. In this study, to investigate the prediction of thoughts, we have used Machine Learning techniques using Naïve Bayes with high accuracy of 98.33%. According to the findings, the data analytics demonstrated that women have a strong interest in careers with Information Technology. A woman has the opportunity to perform and establish her worth if she enters a profession or career. Employees are under pressure to succeed to quickly advance up the corporate ladder. The result of this research can be utilized for the empowerment of women in IT.

Keywords

Bangladesh , Women , Information Technology , Machine learning , Naïve bias

Journal or Conference Name

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA)

Publication Year

2021

Indexing

scopus