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Abstract: We have acquired knowledge through articles and papers on the use of machine learning to anticipate student placement. In our understanding of the education field, it is evident that placement holds importance, for both students and educational institutions. For students it can provide insights into their likelihood of securing placements enabling them to make informed decisions regarding their career paths. Although we are still in the development phase and continuously gaining insights into this matter, we are confident in our potential as a tool, in creating an accurate, reliable and fair student placement prediction portal. Using machine learning we can analyze data related to student performance placement outcomes and other factors. This analysis helps us identify patterns that can inform predictions, about placement success. To gain insights we employ logic techniques to uncover patterns and trends, within large datasets of student information. This valuable knowledge is then utilized in the development of models. Moreover, we used web development technologies to create a user portal where students can conveniently input their data and receive placement predictions.To analyze this data and predict student placement accurately implementing a machine learning algorithm within the portal is necessary. In my understanding of the education field, it is evident that placement holds importance, for both students and educational institutions.For students it can provide insights into their likelihood of securing placements enabling them to make informed decisions regarding their career paths. Ensuring the security of student data is of importance for the portal
Jadhav et al. (Fri,) studied this question.
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