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자료유형
학술저널
저자정보
Sang Pyo Jun (Namseoul University)
저널정보
한국컴퓨터정보학회 한국컴퓨터정보학회논문지 한국컴퓨터정보학회 논문지 제24권 제1호(통권 제178호)
발행연도
2019.1
수록면
257 - 263 (7page)

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This paper is a study on mathematical aspects that can be basic for understanding and applying the contents of machine learning. If you are familiar with mathematics in the field of computer science, you can create algorithms that can diversify researches and implement them faster, so you can implement many real-life ideas. There is no curriculum standard for mathematics in the field of machine learning, and there are many absolutely lacking mathematical contents that are taught in the curriculum presented at existing universities. Machine learning now includes speech recognition systems, search engines, automatic driving systems, process automation, object recognition, and more. Many applications that you want to implement combine a large amount of data with many variables into the components that the programmer generates. In this course, the mathematical areas required for computer engineer (CS) practitioners and computer engineering educators have become diverse and complex. It is important to analyze the mathematical content required by engineers and educators and the mathematics required in the field. This paper attempts to present an effective range design for the essential processes from the basic education content to the deepening education content for the development of many researches.

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Abstract
I. Introduction
Ⅱ. Contents of mathematics related to computer engineering
Ⅲ. Development direction of mathematics curriculum related to machine learning
Ⅳ. The Proposed Scheme
Ⅴ. Simulation
Ⅵ. Conclusions
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