머신러닝 (ML)은 입력 데이터에서 예측을 수행하도록 모델을 학습시키는 프로그램 또는 시스템에 대한 연구 분야입니다. ML은 지도, 번역 앱, 노래 추천 등 일상 생활에 필수가 된 일부 기술을 지원합니다.
이러한 기술을 설명하는 데 사용되는 '인공지능(AI)'이라는 용어도 들어보셨을 것입니다. 공식적으로는 서로 바꿔서 사용되기도 하지만 ML은 AI의 하위 필드로 간주됩니다. 인공지능은 이미지 생성 또는 음성 인식과 같은 정교한 작업을 수행할 수 있는 사람이 아닌 프로그램 또는 모델입니다.
[null,null,["최종 업데이트: 2023-07-25(UTC)"],[[["\u003cp\u003eMachine learning (ML) focuses on training models to make predictions from data, powering technologies like maps and recommendations.\u003c/p\u003e\n"],["\u003cp\u003eArtificial intelligence (AI) encompasses a broader range of sophisticated tasks, with ML being a subfield within it.\u003c/p\u003e\n"],["\u003cp\u003eGoogle provides introductory resources for understanding ML concepts and problem-solving, along with a glossary for key terms.\u003c/p\u003e\n"]]],[],null,["# Machine Learning & Artificial Intelligence Basics\n\nNew to machine learning, or need a refresher? Check out the resources below.\n| **Estimated Read Time:** 10 minutes\n| **Learning objectives:**\n|\n| - Define machine learning and artificial intelligence.\n| - Describe applications of ML and AI.\n\nMachine learning (ML) is the field of study of programs or systems that trains\nmodels to make predictions from input data. ML powers some of the technologies\nthat have become integral to our daily lives, including maps, translation apps,\nand song recommendations, to name a few.\n\nYou may hear the term \"artificial intelligence,\" or AI, used to describe these\ntechnologies as well. Although sometimes used interchangeably, formally, ML is\nconsidered a subfield of AI. Artificial intelligence is a non-human program or\nmodel that can perform sophisticated tasks, such as image generation or speech\nrecognition.\n\nIf you are new to ML, we recommend [Introduction to Machine Learning](https://developers.google.com/machine-learning/intro-to-ml). If you are trying\nto decide whether to use ML to solve a problem, [Introduction to Machine\nLearning Problem Framing](https://developers.google.com/machine-learning/problem-framing) can help get\nyou started.\n\nFor definitions of key concepts in ML, please see [Machine Learning Glossary: ML\nFundamentals](https://developers.google.com/machine-learning/glossary/fundamentals)."]]
