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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 저널정보
- 한국정보통신학회 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING 2019 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING Vo.11 No.1
- 발행연도
- 2019.6
- 수록면
- 147 - 151 (5page)
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초록· 키워드
오류제보하기
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.
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.
목차
Abstract
I. INTRODUCTION
II. DEEPLEARNING
III. RESEARCH METHOD
IV. Design of a Career Prediction Model using Tensorflow
V. CONCLUSION
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2019-004-000919734