데이터 과학과 인공지능 실습 교육을 위한 Orange 플랫폼과 Python 언어의 적용 사례 = Applications of Orange Platform and Python Language to Practice Education of Data Science and Artificial Intelligence

다국어 초록 (Multilingual Abstract)

Artificial intelligence technology is developing rapidly and is becoming common enough to easily utilize artificial intelligence in everyday life. Major countries such as Korea, the United States, China, and Japan are preparing plans to introduce data science and artificial intelligence education as basic education not only in elementary schools but also in secondary schools. Accordingly, various artificial intelligence programs or services, which can be utilized for learning data science and artificial intelligence, are being developed. The
Orange platform and Python Language are open source platforms for data science and artificial intelligence, and can be effectively used in a wide range of fields such as data science and artificial intelligence education. In particular, Orange helps users who are not familiar with data science and artificial intelligence programming to enter artificial intelligence technology because they can create artificial intelligence applications by dragging and connecting visual components called widgets with a mouse. In addition, Orange
not only uses the Python open source library, but also provides various add-ons such as Image Analytics and Text Mining. So it can also be useful for users who are familiar with data science and artificial intelligence. Python is widely known as a programming language for data science and artificial intelligence. It is easy to learn when compared to other languages such as and C or C++. Furthermore, Python provides so many powerful packages for data science and artificial intelligence.
In this thesis, it is presented as cases that Orange platform and Python language are applied to practice of data science and artificial intelligence. In these cases, I introduce applications of Orange to classification of images and analysis of health data, and also an application of Python Language to analysis of big health data. It is hoped that the cases in this thesis are utilized for representative examples to help learners to practice data science and artificial intelligence.

목차 (Table of Contents)

• Ⅰ. 서론 ····················································································································· 1
• Ⅱ. Orange 플랫폼과 Python 언어 ··························································· 3
• 1. Orange 플랫폼의 소개 ···················································································· 3
• 2. Orange 플랫폼의 구성 ···················································································· 3
• 3. Python 언어의 소개 ························································································ 9
• 4. 데이터 과학과 인공지능을 위한 파이썬 패키지 ········································· 9
• 1) Pandas ············································································································· 9
• 2) Matplotlib ······································································································ 10
• 3) Scikit-learn ·································································································· 10
• 4) Numpy ··········································································································· 10
• 5) Seaborn ········································································································· 11
• Ⅲ. Orange를 이용한 인공지능과 데이터 분석 실습 사례 ··········· 11
• 1. Orange를 이용한 이미지 분류 실습 사례 ················································ 11
• 2. Orange를 이용한 건강 데이터 분석 실습 사례 ····································· 14
• 3. Orange 플랫폼을 이용한 실습 사례에 대한 고찰 ··································· 16
• Ⅳ. 파이썬 언어를 이용한 데이터 분석 실습 사례 ··························· 17
• 1. 파이썬 실습 환경 ···························································································· 17
• 2. 표본 코호트 건강 데이터 포맷 ·································································· 17
• 3. 건강 데이터 입력을 위한 파이썬 코드 ··················································· 18
• -i-- ii -
• 4. 분석 데이터 추출 ························································································ 19
• 5. 건강 데이터 분석과 시각화 ······································································ 24
• 6. 파이썬 언어를 이용한 실습 사례에 대한 고찰 ····································· 27
• Ⅴ. 결론 ··················································································································· 29
• 참고문헌 ·················································································································· 30
• 부록 ··························································································································· 31