ICFICE 2019
Current Result Document :
| 한글제목(Korean Title) |
Design of Prediction of Student Career Model Using Tensorflow based Deeplearning |
| 영문제목(English Title) |
Design of Prediction of Student Career Model Using Tensorflow based Deeplearning |
| 저자(Author) |
Geun-Ho Kim
Eui-Jeong Kim
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| 원문수록처(Citation) |
VOL 11 NO. 01 PP. 0147 ~ 0151 (2019. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
In the wake of the fourth industrial revolution, the question of career education has become a big issue in school education. Various studies have been conducted on services or technologies to effectively handle artificial intelligence and big data in the field, but in the field of education, data on students is only simplified. In this paper, we intend to design a career prediction model for students' career education through deep learning using Tenserflow. Using observational data of gifted and talented students, try deep learning using Tenserflow, which is considered the most widely used and efficient of the deep learning framework, and predict the course of students. Deep learning results showed accuracy of over 70% and near rmsedms 1. Therefore, as shown in this study, many studies and data will be constructed to help present the course of use for student counseling and to provide classroom attitudes and directions.
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| 키워드(Keyword) |
Deep learning
Big data
AI
Predict the career
Tensorflow
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| 파일첨부 |
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