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머신 러닝 프로젝트 구조화

Andrew Ng

딥 러닝 전문화 과정의 세 번째 과정에서는 성공적인 머신 러닝 프로젝트를 구축하고 머신 러닝 프로젝트 리더로서 의사 결정을 연습하는 방법을 배우게 됩니다.

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딥 러닝 전문화 과정의 세 번째 과정에서는 성공적인 머신 러닝 프로젝트를 구축하고 머신 러닝 프로젝트 리더로서 의사 결정을 연습하는 방법을 배우게 됩니다.

이 과정을 마치면 머신 러닝 시스템의 오류를 진단할 수 있고, 오류를 줄이기 위한 전략의 우선 순위를 지정하고, 일치하지 않는 training/test set와 같은 복합적인 ML 설정을 이해하며 휴먼 레벨의 성능에 필적 및/또는 능가하는 ML 설정을 이해하고, 종단 간 학습, 전이 학습, 멀티 태스크 러닝을 적용할 수 있게 됩니다.

이는 또한 기본적인 머신 러닝 지식이 있는 학습자를 위한 독립형 과정입니다. 이 과정에서는 많은 딥 러닝 제품을 구축하고 출시한 Andrew Ng의 경험을 활용합니다. AI 팀의 방향을 제시할 수 있는 기술 리더가 되고 싶다면 이 과정은 수년간의 ML 업무 경험을 거친 후에 얻을 수 있는 ‘산업 경험’을 제공해드립니다.

딥 러닝 전문화 과정은 딥 러닝의 기능, 도전 과제 및 결과를 이해하고 첨단 AI 기술 개발에 참여할 수 있도록 준비하는 데 도움이 되는 기본 프로그램입니다. 머신 러닝을 업무에 적용하고, 기술 경력의 수준을 높이고, AI 세계의 최종적인 단계를 밟을 수 있는 지식과 기술을 쌓을 수 있는 경로를 제공합니다.

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What's inside

Syllabus

ML 전략(1)
목표 설정을 위한 전략적 지침을 구현하고 휴먼 레벨의 성능을 적용하여 주요 우선 순위를 정의함으로써 ML 프로덕션 워크플로를 간소화하고 최적화합니다.
ML 전략(2)
시간을 절약할 수 있는 오류 분석 절차를 개발하여 추구할 가치가 가장 높은 옵션을 평가하고 데이터를 분할하는 방법과 멀티 태스크, 전이 및 종단간 딥 러닝을 사용할 시기에 대한 직관력을 가지게 됩니다.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
이 과정은 머신러닝과 딥러닝의 기본 지식이 있는 학습자를 대상으로 합니다
이 과정은 안드루 응(Andrew Ng)가 강의합니다. 그는 딥러닝 분야의 저명한 전문가입니다
이 과정은 성공적인 머신러닝 프로젝트를 구축하고 머신러닝 프로젝트 리더로서 의사 결정을 연습하는 데 중점을 둡니다
이 과정을 통해 학습자는 머신러닝 시스템의 오류를 진단하고, 오류를 줄이기 위한 전략을 우선 순위를 정하고, 휴먼 레벨의 성능에 필적하고/또는 능가하는 ML 설정을 이해할 수 있습니다
이 과정은 종단 간 학습, 전이 학습, 멀티 태스크 러닝과 같은 최신 머신러닝 기법을 소개합니다

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Activities

Coming soon We're preparing activities for 머신 러닝 프로젝트 구조화. These are activities you can do either before, during, or after a course.

Career center

Learners who complete 머신 러닝 프로젝트 구조화 will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning algorithms to solve complex problems. This course can help Machine Learning Engineers build a foundation in organizing and managing machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course can also help Machine Learning Engineers develop the skills they need to work independently and as part of a team.
Data Scientist
Data Scientists use data to solve business problems. This course can help Data Scientists develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course can also help Data Scientists learn how to work independently and as part of a team.
Product Manager
Product Managers are responsible for the development and launch of new products. This course can help Product Managers develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course can also help Product Managers learn how to work independently and as part of a team.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help Software Engineers build a foundation in organizing and managing machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course may also help Software Engineers develop the skills they need to work independently and as part of a team.
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course can help Data Analysts develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course can also help Data Analysts develop the skills they need to work independently and as part of a team.
Consultant
Consultants help businesses and organizations solve problems and improve performance. This course can help Consultants develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course may also help Consultants develop the skills they need to work independently and as part of a team.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course may help Quantitative Analysts develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. However, this course may not cover the specific mathematical and statistical models used by Quantitative Analysts.
Technical Writer
Technical Writers create documentation and other materials to help users understand and use products and services. This course may help Technical Writers develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. However, this course may not cover the specific writing and communication skills needed by Technical Writers.
Teacher
Teachers teach students in classrooms and other settings. This course may help Teachers develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. However, this course may not cover the specific teaching and communication skills needed by Teachers.
Researcher
Researchers conduct studies to answer questions and develop new knowledge. This course may help Researchers develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. However, this course may not cover the specific research methods and techniques used by Researchers.
Project Manager
Project Managers plan, organize, and execute projects. This course can help Project Managers develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course can also help Project Managers learn how to work independently and as part of a team.
Trainer
Trainers teach others how to use products, services, and skills. This course may help Trainers develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. However, this course may not cover the specific teaching and communication skills needed by Trainers.
Business Analyst
Business Analysts help businesses identify and solve problems. This course can help Business Analysts develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. This course may also help Business Analysts develop the skills they need to work independently and as part of a team.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to improve the efficiency of organizations. This course may help Operations Research Analysts develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. However, this course may not cover the specific mathematical and analytical methods used by Operations Research Analysts.
Statistician
Statisticians collect, analyze, and interpret data to help businesses and organizations make informed decisions. This course may help Statisticians develop the skills they need to organize and manage machine learning projects. They will learn how to set goals, prioritize tasks, and track progress. However, this course may not cover the specific statistical methods used by Statisticians.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in 머신 러닝 프로젝트 구조화.
이 책은 파이썬을 사용하여 딥러닝 모델을 구축하는 방법을 안내하는 책입니다. 이 과정의 딥러닝 관련 주제를 보완하는 데 도움이 될 수 있습니다.
Provides a comprehensive overview of statistical learning methods, including supervised and unsupervised learning. It can be a valuable reference for the ML Strategy modules in this course, providing a deeper understanding of the statistical foundations of machine learning.
이 책은 패턴 인식과 머신 러닝의 수학적 기반을 설명하는 책입니다. 이 과정의 ML 전략 모듈에 도움이 될 수 있는 배경 지식을 제공합니다.
Python 기반의 ML 라이브러리와 기술을 소개하는 책으로, ML 모델의 구축 및 배포를 위한 실용적인 지침을 제공합니다.
R 기반의 ML 기술과 알고리즘을 다루는 책으로, ML 모델의 개발 및 구축을 위한 실용적인 지침을 제공합니다.

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