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표준 체계 › IT·데이터 기술

표시명 (언어별)

언어당 대표 표시명은 하나다. 언어를 늘리는 것은 이 표에 행을 넣는 일이다.

언어	표시명	대표
English	Machine Learning	대표
한국어	머신러닝	대표

언어

표시명

대표

English

Machine Learning

대표

한국어

머신러닝

대표

표기형

regex 는 사람이 쓴 매칭 패턴, term 은 말뭉치에서 실제로 관측된 표기, alias 는 검색 전용 동의어다. 42개

언어	종류	표기	관측 공고
mul	regex	딥러닝	—
mul	regex	머신러닝	—
mul	regex	deep learning	—
mul	regex	machine learning	—
mul	regex	pytorch	—
mul	regex	scikit-?learn	—
mul	regex	tensorflow	—
ko	alias	모델링	—
ko	alias	수요 예측	—
ko	alias	예측 모델	—
ko	alias	AI 모델	—
en	term	machine learning	8
en	term	tensorflow	3
en	term	deep learning	2
en	term	scikit-learn	2
ko	term	딥러닝	1
ko	term	머신러닝 등을 이용 개발	1
ko	term	딥러닝 등 연구개발	1
ko	term	딥러닝 등 연구개발 경력 2년	1
en	term	ai engineering data science machine learning	1
en	term	cloud machine learning	1
en	term	computer science artificial intelligence machine learning	1
en	term	data science or machine learning	1
en	term	deep learning libraries	1
en	term	deploying machine learning models	1
en	term	gpu-accelerated deep learning frameworks	1
en	term	knowledge of statistical/machine learning tools	1
en	term	machine learning data science	1
en	term	machine learning models	1
en	term	machine learning techniques	1
en	term	machine learning tools	1
en	term	mlops/mllops for maintaining machine learning lifecycle	1
en	term	predictive modeling machine learning	1
en	term	pytorch	1
en	term	pytorch and tensorflow	1
en	term	r scikit-learn etc	1
en	term	sas r tensorflow	1
en	term	statistical and machine learning models	1
en	term	statistical and machine learning techniques	1
en	term	statistical/machine learning tools	1
ko	term	tensorflow	1
en	term	tensorflow scikit-learn langchain openai apis	1

언어

종류

표기

관측 공고

mul

regex

딥러닝

—

mul

regex

머신러닝

—

mul

regex

deep learning

—

mul

regex

machine learning

—

mul

regex

pytorch

—

mul

regex

scikit-?learn

—

mul

regex

tensorflow

—

alias

모델링

—

alias

수요 예측

—

alias

예측 모델

—

alias

AI 모델

—

term

machine learning

term

tensorflow

term

deep learning

term

scikit-learn

term

딥러닝

term

머신러닝 등을 이용 개발

term

딥러닝 등 연구개발

term

딥러닝 등 연구개발 경력 2년

term

ai engineering data science machine learning

term

cloud machine learning

term

computer science artificial intelligence machine learning

term

data science or machine learning

term

deep learning libraries

term

deploying machine learning models

term

gpu-accelerated deep learning frameworks

term

knowledge of statistical/machine learning tools

term

machine learning data science

term

machine learning models

term

machine learning techniques

term

machine learning tools

term

mlops/mllops for maintaining machine learning lifecycle

term

predictive modeling machine learning

term

pytorch

term

pytorch and tensorflow

term

r scikit-learn etc

term

sas r tensorflow

term

statistical and machine learning models

term

statistical and machine learning techniques

term

statistical/machine learning tools

term

tensorflow

term

tensorflow scikit-learn langchain openai apis

외부 표준 대응

대응 유형은 SKOS 매핑 술어를 그대로 쓴다 — 정확대응이 아닌 것을 정확대응으로 적어 두면 그 차이를 되살릴 방법이 없다. 0건

아직 대응이 없다. ESCO·O*NET·ICAO 역량체계와의 대응은 사람이 확정한다.

도출 근거

이 개념으로 묶인 용어 후보와, 그 용어가 처음 관측된 원문 문장.

용어	언어	공고	항공사	원문 근거
machine learning	en	8	6	Experience in Machine Learning, Data Science, and AI-driven techniques
tensorflow	en	3	2	Proficiency with AI/ML frameworks and tools (e.g., TensorFlow, scikit-learn, LangChain, OpenAI APIs) is a strong advantage.
scikit-learn	en	2	2	Proficiency with AI/ML frameworks and tools (e.g., TensorFlow, scikit-learn, LangChain, OpenAI APIs) is a strong advantage.
deep learning	en	2	2	Hands-on experience with machine learning, deep learning, natural language processing (NLP), GenAI, recommender systems, experimentation (e.g., A/B testing).
tensorflow scikit-learn langchain openai apis	en	1	1	Proficiency with AI/ML frameworks and tools (e.g., TensorFlow, scikit-learn, LangChain, OpenAI APIs) is a strong advantage.
gpu-accelerated deep learning frameworks	en	1	1	Highly conversant with GPU-accelerated deep learning frameworks (such as PyTorch and TensorFlow).
pytorch and tensorflow	en	1	1	Highly conversant with GPU-accelerated deep learning frameworks (such as PyTorch and TensorFlow).
pytorch	en	1	1	Highly conversant with GPU-accelerated deep learning frameworks (such as PyTorch and TensorFlow).
predictive modeling machine learning	en	1	1	Experience in advanced analytics and data science, including predictive modeling, machine learning, and statistical analysis (Preferred)
statistical/machine learning tools	en	1	1	Working knowledge of statistical/machine learning tools (e.g., SAS, R, TensorFlow) preferred
machine learning tools	en	1	1	Working knowledge of statistical/machine learning tools (e.g., SAS, R, TensorFlow) preferred
sas r tensorflow	en	1	1	Working knowledge of statistical/machine learning tools (e.g., SAS, R, TensorFlow) preferred
knowledge of statistical/machine learning tools	en	1	1	Working knowledge of statistical/machine learning tools (e.g., SAS, R, TensorFlow) preferred
ai engineering data science machine learning	en	1	1	4–7+ years of industry experience in AI engineering, data science, machine learning, or applied advanced analytics, including production model deployment.
cloud machine learning	en	1	1	Relevant cloud, machine learning, or MLOps certification.
data science or machine learning	en	1	1	At least 3 years of commercial experience in Data Science or Machine Learning
r scikit-learn etc	en	1	1	Experience with statistical packages (e.g. R, scikit-learn, etc.)
mlops/mllops for maintaining machine learning lifecycle	en	1	1	Experience with MLOps/MLLops for maintaining machine learning lifecycle.
computer science artificial intelligence machine learning	en	1	1	Bachelor’s or Master’s degree in computer science, Artificial Intelligence, Machine Learning, or related field.
deep learning libraries	en	1	1	More than 3 years' experience with Python, SQL and popular machine/deep learning libraries.
statistical and machine learning models	en	1	1	Proficient with statistical and machine learning models (both supervised and unsupervised learning).
machine learning models	en	1	1	Proficient with statistical and machine learning models (both supervised and unsupervised learning).
딥러닝 등 연구개발	ko	1	1	ㆍAI 유관 전공(AI, 컴퓨터공학, S/W, 데이터 등) 석사 학위 이상 보유자 또는 AI 관련 분야(AI, 자율비행, 딥러닝 등) 연구개발 경력 2년 이상 보유자
딥러닝 등 연구개발 경력 2년	ko	1	1	ㆍAI 유관 전공(AI, 컴퓨터공학, S/W, 데이터 등) 석사 학위 이상 보유자 또는 AI 관련 분야(AI, 자율비행, 딥러닝 등) 연구개발 경력 2년 이상 보유자
딥러닝	ko	1	1	ㆍ딥러닝/AI 기반 통신 응용 프로젝트 개발 경험
tensorflow	ko	1	1	ㆍPython, Pytorch, Tensorflow, GitHub, FastAPI 기반 개발 경력을 보유하신 분
machine learning data science	en	1	1	Experience in Machine Learning, Data Science, and AI-driven techniques
머신러닝 등을 이용 개발	ko	1	1	ㆍAI/머신러닝 등을 이용 개발 경험이 있으신 분
statistical and machine learning techniques	en	1	1	Deep knowledge of statistical and machine learning techniques
machine learning techniques	en	1	1	Deep knowledge of statistical and machine learning techniques
deploying machine learning models	en	1	1	Practical experience in designing, building and deploying machine learning models.