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이 과정에서는 딥 러닝을 사용해 이미지 캡션 모델을 만드는 방법을 알아봅니다. 인코더 및 디코더와 모델 학습 및 평가 방법 등 이미지 캡션 모델의 다양한 구성요소에 대해 알아봅니다. 이 과정을 마치면 자체 이미지 캡션 모델을 만들고 이를 사용해 이미지의 설명을 생성할 수 있게 됩니다.
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What's inside
Syllabus
이미지 캡션 모델 만들기: 개요
이 모듈에서는 딥 러닝을 사용해 이미지 캡션 모델을 만드는 방법을 설명합니다. 인코더 및 디코더와 모델 학습 및 평가 방법 등 이미지 캡션 모델의 다양한 구성요소에 대해 알아봅니다. 이 모듈을 마치면 자체 이미지 캡션 모델을 만들고 이를 사용해 이미지의 설명을 생성할 수 있게 됩니다.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a straightforward approach to creating image caption models using deep learning
Involves hands-on experience in building and evaluating image caption models using practical components like encoders and decoders
Suitable for learners with a foundation in deep learning and neural networks
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Activities
Be better prepared
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during
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after
it. Supplement your coursework and achieve mastery of the topics covered
in Create Image Captioning Models - 한국어 with these
activities:
경험 있는 이미지 캡션 개발자 찾기
Show steps
이미지 캡션 모델링 분야에서 실적이 있는 경험자나 멘토를 찾아 기술적 지침과 지원을 받습니다.
Show steps
-
잠재적 멘토 식별
-
연락하기 및 멘토십 요청
-
멘토와 정기적으로 만나 지도를 받음
피어 학습 그룹에 참여하기
Show steps
이미지 캡션 모델에 대해 공부하고 있는 동료 학생들과 함께 그룹을 만들어 지식을 공유하고 지원을 제공합니다.
Show steps
-
피어 학습 그룹 찾기 또는 구성
-
정기적인 회의 일정
-
프로젝트 아이디어 공유 및 협업
디코더 구현을 위한 튜토리얼 따라가기
Show steps
인코더에서 출력된 특징을 캡션으로 변환하는 디코더 구현에 대해 단계별 지침을 제공하는 튜토리얼을 통해 핵심 개념과 기술을 강화합니다.
Show steps
-
튜토리얼 찾기 및 선택
-
디코더 구현 지침 따르며 구현
-
디코더 성능 평가
Two other activities
Expand to see all activities and additional details
Show all five activities
소규모 이미지 캡션 프로젝트 시작
Show steps
소규모 이미지 캡션 프로젝트를 시작하여 이미지 캡션 모델 구축에 대한 실제 경험을 얻고 기술을 적용하는 능력을 기릅니다.
Show steps
-
프로젝트 범위 및 목표 정의
-
데이터셋 수집 또는 생성
-
모델 훈련 및 평가
이미지 캡션 모델링 워크숍 참석
Show steps
이미지 캡션 모델링 분야의 전문가가 주도하는 워크숍에 참석하여 첨단 기술과 모범 사례에 대해 배울 수 있는 기회를 제공합니다.
Show steps
-
주요 발표 및 워크샵 세션 참석
-
전문가와 네트워킹
-
워크숍에서 습득한 내용을 프로젝트에 적용
경험 있는 이미지 캡션 개발자 찾기
Show steps
이미지 캡션 모델링 분야에서 실적이 있는 경험자나 멘토를 찾아 기술적 지침과 지원을 받습니다.
Show steps
Show steps
Show steps
- 잠재적 멘토 식별
- 연락하기 및 멘토십 요청
- 멘토와 정기적으로 만나 지도를 받음
피어 학습 그룹에 참여하기
Show steps
이미지 캡션 모델에 대해 공부하고 있는 동료 학생들과 함께 그룹을 만들어 지식을 공유하고 지원을 제공합니다.
Show steps
Show steps
Show steps
- 피어 학습 그룹 찾기 또는 구성
- 정기적인 회의 일정
- 프로젝트 아이디어 공유 및 협업
디코더 구현을 위한 튜토리얼 따라가기
Show steps
인코더에서 출력된 특징을 캡션으로 변환하는 디코더 구현에 대해 단계별 지침을 제공하는 튜토리얼을 통해 핵심 개념과 기술을 강화합니다.
Show steps
Show steps
Show steps
- 튜토리얼 찾기 및 선택
- 디코더 구현 지침 따르며 구현
- 디코더 성능 평가
Two other activities
Expand to see all activities and additional details
Show all five activities
소규모 이미지 캡션 프로젝트 시작
Show steps
소규모 이미지 캡션 프로젝트를 시작하여 이미지 캡션 모델 구축에 대한 실제 경험을 얻고 기술을 적용하는 능력을 기릅니다.
Show steps
Show steps
Show steps
- 프로젝트 범위 및 목표 정의
- 데이터셋 수집 또는 생성
- 모델 훈련 및 평가
이미지 캡션 모델링 워크숍 참석
Show steps
이미지 캡션 모델링 분야의 전문가가 주도하는 워크숍에 참석하여 첨단 기술과 모범 사례에 대해 배울 수 있는 기회를 제공합니다.
Show steps
Show steps
Show steps
- 주요 발표 및 워크샵 세션 참석
- 전문가와 네트워킹
- 워크숍에서 습득한 내용을 프로젝트에 적용
Career center
Learners who complete Create Image Captioning Models - 한국어 will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers use artificial intelligence and machine learning to make sense of visual data. They may work with images or video footage. Computer Vision Engineers are able to help a computer understand and classify a multitude of images provided they have been trained on similar imagery. CNNs and the creation of image captions are both at the heart of what Computer Vision Engineers do. After taking this course, you will be well equipped to step into an entry-level Computer Vision Engineering position.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and implement new machine learning algorithms and models. They will also ensure that these models are able to be deployed into production. Image captioning is but one element of real-world machine learning applications. This course may be helpful as it provides entry-level foundational knowledge taught by actual staff at Google Cloud. If you are interested in a career as a Machine Learning Engineer, taking this course demonstrates passion for the field.
Computer Vision Researcher
Computer Vision Researcher
Computer Vision Researchers are responsible for pushing the boundaries of what computer vision can do. They develop new algorithms and models to improve the accuracy and efficiency of computer vision systems. This course may be helpful for an aspiring researcher as it provides a solid theoretical foundation for the real-world applications of image captioning.
Image Processing Engineer
Image Processing Engineer
Image Processing Engineers have a solid foundation in computer science, signal processing, and computer vision. They are responsible for designing and implementing systems that can process images and extract meaningful information. This course helps to lay the groundwork for a future career in Image Processing Engineering. However, to step into this role, an advanced degree is usually required.
Data Scientist
Data Scientist
Data Scientists are responsible for extracting knowledge from data using scientific methods, often to create machine learning models. Data Scientists have a broad skill set including machine learning, data analysis, and statistics. This course may be helpful for a Data Scientist who is looking to step into a more specialized role within Computer Vision. A Data Scientist with knowledge of image captioning is a highly specialized and desirable candidate.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and implement artificial intelligence systems. They may work on a variety of projects, from self-driving cars to medical diagnosis systems. This course can help to build a foundation for a career in AI Engineering by introducing the fundamental concepts of image captioning, a common real-world application of AI.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, build, and maintain robots. They may work on a variety of robots, from industrial robots to medical robots. This course may be helpful as it provides insights into the specialized area of image captioning in robotics. A Robotics Engineer who understands image captioning is able to design robots that can more effectively interact with the world around them.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers design and implement systems that can understand and generate human language. This course may be helpful for a NLP Engineer who is looking to advance into the specialized area of image captioning. NLP Engineers with image captioning skills are able to build more sophisticated systems that can process and understand visual data.
Computer Programmer
Computer Programmer
Computer Programmers write and maintain the code that powers our world. They may work on a variety of projects, from developing new software applications to maintaining existing systems. This course may be helpful as it will introduce basic concepts of image captioning, a real-world use case for computer programmers. Furthermore, this course is taught by Google Cloud, a corporation highly sought after by Computer Programmers.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They may work on a variety of projects, from developing new software applications to maintaining existing systems. This course is taught by Google Cloud, a corporation highly sought after by Software Engineers.
Web Developer
Web Developer
Web Developers design and develop websites and web applications. This course may be helpful as it provides entry-level basics of image captioning, a common problem Web Developers encounter. Employers value candidates with knowledge of Google Cloud.
Systems Administrator
Systems Administrator
Systems Administrators are responsible for the installation, configuration, and maintenance of computer systems. This course may be helpful as it introduces basic concepts of image captioning. As an added bonus, the course is taught by Google Cloud, a corporation highly sought after by Systems Administrators.
Security Analyst
Security Analyst
Security Analysts are responsible for the design, implementation, and maintenance of computer security systems. This course may be helpful as it introduces basic concepts of image captioning, a valuable skillset that can be applied to security analysis.
Database Administrator
Database Administrator
Database Administrators are responsible for the design, implementation, and maintenance of databases. This course may be helpful as it introduces basic concepts of image captioning, a valuable skillset that can be applied to database management.
Network Administrator
Network Administrator
Network Administrators are responsible for the design, implementation, and maintenance of computer networks. This course may be helpful as it introduces basic concepts of image captioning, a valuable skillset that can be applied to network management.
For more career information including salaries, visit:
OpenCourser.com/course/z48f1z/create
Reading list
We've selected ten 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
Create Image Captioning Models - 한국어.
Save
이 책은 자연어 처리에 대한 포괄적인 안내서이며 이미지 캡션과 같은 작업에 대한 딥 러닝 접근 방식을 설명합니다.
Save
이 책은 생성 모델과 이미지 캡션에 대한 딥 러닝 접근 방식을 다룹니다.
이 책은 Keras 프레임워크를 사용하여 이미지 캡션과 같은 딥 러닝 모델을 구축하는 방법을 설명합니다.
이 책은 컴퓨터 비전에 대한 딥 러닝 접근 방식을 다루며 이미지 캡션과 같은 작업에 대한 실용적인 가이드를 제공합니다.
이 책은 컴퓨터 비전의 기본 개념과 알고리즘을 다루며 이미지 캡션과 관련된 주제를 다룹니다.
이 책은 자연어 처리의 기본 개념과 알고리즘을 다루며 이미지 캡션과 관련된 주제를 다룹니다.
이 책은 딥 러닝의 기본 개념과 알고리즘을 다루며 이미지 캡션과 관련된 주제에 대한 소개를 제공합니다.
Save
이 책은 컴퓨터 비전의 기본 개념과 알고리즘을 다루며 이미지 캡션과 관련된 주제를 다룹니다.
이 책은 패턴 인식과 머신 러닝의 기본 개념과 알고리즘을 다루며 이미지 캡션과 관련된 주제를 다룹니다.
이 책은 말과 언어 처리의 기본 개념과 알고리즘을 다루며 이미지 캡션과 관련된 주제를 다룹니다.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/z48f1z/create
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Level
Advanced
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Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
한국어
Good to know
Provides a straightforward approach to creating image caption models using deep learning
Involves hands-on experience in building and evaluating image caption models using practical components like encoders and decoders
Suitable for learners with a foundation in deep learning and neural networks
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