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Machine Learning Approach to Predict SGPA and CGPA

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dc.contributor.author Saifuzzaman, Mohd.
dc.contributor.author Parvin, Masuma
dc.contributor.author Jahan, Israt
dc.contributor.author Moon, Nazmun Nessa
dc.contributor.author Nur, Fernaz Narin
dc.contributor.author Shetu, Syeda Farjana
dc.date.accessioned 2022-04-04T03:54:54Z
dc.date.available 2022-04-04T03:54:54Z
dc.date.issued 2021-07-30
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7723
dc.description.abstract The prediction of SGPA and CGPA is beneficial to university students. Students will easily get an estimate of their final outcome from this project. As a result, the students will be able to brace themselves for a successful outcome. Students pass the day by participating in a variety of events. Students use social media sites such as Facebook, Instagram, and Twitter. They engage in various hobbies such as playing mobile games, listening to music, among others. As a result, they were able to move several times with these tasks. As a result, if a student spends so much time doing any of those things, she will not be able to achieve a successful grade because of the experiment; students can develop a research routine or guideline that they can apply to their other tasks. Additionally, students' behaviors will forecast their outcomes. The Authors will now see machine learning in Python being used all over the place. After that, The Authors created a smart SGPA and CGPA prediction project, as well as the results on students. The findings are predicted using the Nave Byes algorithm. The Nave Byes algorithm is a simple but effective prediction algorithm. It is a machine learning algorithm as well. As a result, students will be given an estimate of their final exam scores. They can prepare them to make a good result by following the routine of the SGPA & CGPA prediction project. en_US
dc.language.iso en_US en_US
dc.publisher 2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST), IEEE en_US
dc.subject Machine learning algorithms en_US
dc.subject Social networking (online) en_US
dc.subject Multimedia web sites en_US
dc.subject Music en_US
dc.subject Machine learning en_US
dc.subject Games en_US
dc.subject Prediction algorithms en_US
dc.title Machine Learning Approach to Predict SGPA and CGPA en_US
dc.type Article en_US

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