TensorFlow 2 시작하기 from Coursera

What's inside

Syllabus

TensorFlow 소개

TensorFlow는 딥 러닝을 위한 가장 인기 있는 라이브러리 중 하나이며 오늘날 모든 수준의 연구원과 전문가 사이에서 널리 사용됩니다. 이번 주에는 Coursera 플랫폼에서 TensorFlow 사용을 시작하고 과정 구조에 익숙해지는 훈련을 할 것입니다. 또한 Google Colab을 포함하여 TensorFlow에서 딥 러닝 모델을 개발할 때 유용한 리소스에 대해서도 배우게 됩니다. 이번 주는 과정의 다음 주에 TensorFlow에 진입할 수 있도록 실제로 모든 것을 설정하는 것입니다.

순차 모델 API

TensorFlow에서 딥 러닝 모델을 구축하고 적용하는 방법에는 높은 수준의 빠르고 사용하기 쉬운 API부터 낮은 수준의 작업에 이르기까지 여러 가지가 있습니다. 이번 주에는 딥 러닝 모델에서 빠르게 구축, 훈련, 평가 및 예측하기 위해 고급 Keras API를 사용하는 방법을 배웁니다. 이번 주 프로그래밍 과제는 이 모든 것을 실제로 적용하고 MNIST의 필기 영상 데이터 세트에서 처음부터 이미지 분류 모델을 개발할 수 있는 기회를 제공합니다.

검증, 정규화 및 콜백

모델 검증 및 선택은 과적합을 방지하고 일반화를 개선하는 데 도움이 되는 모든 머신 러닝 모델 개발을 개발하는 데 필수적인 부분입니다. 이번 주에는 훈련 실행에서 검증 데이터 세트를 사용하고 모델에 정규화 기술을 적용하는 방법을 배우게 됩니다. 또한 콜백을 사용하여 성능을 모니터링하고 지정된 기준에 따라 작업을 수행하는 방법을 배우게 됩니다. 이번 주 프로그래밍 과제에서는 잘 알려진 Iris 데이터 세트에서 모델 검증 및 정규화를 실행합니다.

모델 저장 및 로드

딥 러닝 모델 개발의 일부로 지정하려는 특정 기준에 따라 TensorFlow 모델을 저장하고 로드할 수 있어야 합니다. 이번 주에는 콜백을 사용하여 모델을 저장하는 방법, 수동 저장 및 로드, 가중치만 저장하는 것을 포함하여 모델을 저장할 때 사용할 수 있는 옵션을 배우게 됩니다. 또한 사전 훈련된 딥 러닝 모델을 로드하고 사용하는 방법을 연습합니다. 이번 주 프로그래밍 과제에서는 위성 이미지로 훈련된 모델에 대한 유연한 모델 저장 및 로드 구현을 작성합니다.

Capstone 프로젝트

이 과정에서는 Tensorflow에서 딥 러닝 모델을 개발하기 위한 엔드-투-엔드 워크플로우를 배웠습니다. Capstone 프로젝트는 스트리트 뷰 집 번호의 레이블이 지정된 이미지 데이터 세트에 대한 딥 러닝 분류기를 개발하기 위해 모든 지식을 결합할 수 있는 기회를 제공합니다.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers image classification, which is standard in the computer vision domain

Emphasizes hands-on practice through practical coding tutorials and assignments

Provides various ways to build, train, and evaluate TensorFlow models using both high-level APIs and low-level operations

Covers essential concepts for model development such as validation, regularization, and callbacks

Includes a capstone project that involves building a deep learning model for image classification

Prereq: Experience with TensorFlow 1.x or no prior experience is required

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in TensorFlow 2 시작하기 with these activities:

TensorFlow 자료 모음 생성하기

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TensorFlow 자료 모음을 만들면 유용한 리소스와 도구를 한 곳에 모아 학습에 활용할 수 있습니다.

Browse courses on TensorFlow

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온라인에서 TensorFlow 관련 리소스 수집
리소스 정리 및 분류
노트북 또는 온라인 플랫폼에 자료 모음 저장

텐서플로우 2 최신 책 리뷰

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이 책 리뷰에서는 TensorFlow 2의 주요 개념과 특징에 대해 알아보고 코스에서 다루는 주제를 미리 예습하는 데 도움이 됩니다.

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인트로덕션 및 TensorFlow 기본 사항 챕터 읽기
신경망에 대한 챕터 읽기
TensorFlow를 사용한 이미지 분류 모델 구축
리뷰에 대해 간단한 요약 작성

온라인 튜토리얼 및 코스 탐구하기

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온라인 튜토리얼과 코스는 TensorFlow 기술을 확장하고 학습한 개념을 강화하는 데 도움이 될 수 있습니다.

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Coursera, Udemy 또는 edX에서 튜토리얼 및 코스 찾기
관심 있는 튜토리얼 또는 코스 선택
튜토리얼 또는 코스 완료

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코딩 연습 문제 풀기

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코딩 연습 문제를 풀어보면 TensorFlow를 사용하여 딥 러닝 모델을 구축하고 훈련하는 방법에 대한 실습 경험을 쌓을 수 있습니다.

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TensorFlow 웹사이트에서 연습 문제 찾기
문제 풀기
코드 검토 및 디버깅

연습 문제 풀기 그룹 참여하기

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연습 문제 그룹에 참여하면 다른 학생들과 협력하여 문제를 해결하고 학습한 내용을 강화할 수 있습니다.

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학습 관리 시스템 또는 온라인 포럼에서 연습 문제 그룹 찾기
그룹에 가입 및 소개하기
문제 풀기 및 아이디어 공유하기

이미지 분류 프로젝트 시작하기

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이미지 분류 프로젝트를 시작하면 TensorFlow에서 딥 러닝 모델을 구축하고 훈련하는 방법에 대한 실습적 이해를 얻을 수 있습니다.

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데이터셋 선택 및 수집
TensorFlow 모델 선택 및 구축
모델 훈련 및 평가
결과 분석 및 시각화

블로그 게시물 또는 기사 작성

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TensorFlow에 대한 블로그 게시물이나 기사를 작성하면 학습한 내용을 통합하고 지식을 공고히하는 데 도움이 됩니다.

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TensorFlow에서 다루는 주제 선택
조사 및 쓰기
블로그 또는 온라인 플랫폼에 게시
피드백 수집 및 업데이트

TensorFlow 커뮤니티에 기여하기

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TensorFlow 커뮤니티에 기여하면 실제 프로젝트에서 TensorFlow를 사용하여 실무 경험을 쌓을 수 있습니다.

Browse courses on TensorFlow

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GitHub에서 TensorFlow 리포지토리 찾기
문제 확인 또는 기능 제안
풀 리퀘스트 제출
코드 검토 및 합병

Career center

Learners who complete TensorFlow 2 시작하기 will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers design, build, and deploy machine learning models. They work with data scientists to identify business problems that can be solved with machine learning, and then they develop and implement the models that solve those problems. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for solving complex problems. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Machine Learning Engineer.

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Data Scientist

Data Scientists analyze large datasets to uncover patterns, trends, and other useful information. They use their findings to help businesses make better decisions, develop new products, and improve customer service. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Data Scientist.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for developing complex software applications. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Software Engineer.

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Artificial Intelligence Engineer

Artificial Intelligence Engineers design, develop, and maintain artificial intelligence systems. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for developing complex artificial intelligence systems. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Artificial Intelligence Engineer.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to help businesses make better decisions, develop new products, and improve customer service. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Data Analyst.

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Natural Language Processing Engineer

Natural Language Processing Engineers design, develop, and maintain natural language processing systems. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for developing complex natural language processing systems. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Natural Language Processing Engineer.

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Computer Vision Engineer

Computer Vision Engineers design, develop, and maintain computer vision systems. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for developing complex computer vision systems. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Computer Vision Engineer.

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Speech Recognition Engineer

Speech Recognition Engineers design, develop, and maintain speech recognition systems. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for developing complex speech recognition systems. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Speech Recognition Engineer.

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Actuary

Actuaries use mathematics to assess risk and make financial decisions. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large insurance datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Actuary.

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Operations Research Analyst

Operations Research Analysts use mathematical models to solve complex problems. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for solving complex optimization problems. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Operations Research Analyst.

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Financial Analyst

Financial Analysts use data to evaluate investments and make recommendations to clients. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large financial datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Financial Analyst.

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Quantitative Analyst

Quantitative Analysts use mathematics and statistics to analyze financial data. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large financial datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Quantitative Analyst.

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Business Intelligence Analyst

Business Intelligence Analysts use data to identify trends and patterns. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large business datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Business Intelligence Analyst.

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Bioinformatics Scientist

Bioinformatics Scientists use computational methods to analyze biological data. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large biological datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Bioinformatics Scientist.

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Data Warehouse Architect

Data Warehouse Architects design and build data warehouses. They work with a variety of programming languages and technologies, including TensorFlow 2. TensorFlow 2 is a popular library for deep learning, a type of machine learning that is well-suited for analyzing large datasets. This course provides a comprehensive introduction to TensorFlow 2, including how to build, train, and evaluate deep learning models. Taking this course can help you develop the skills needed to become a successful Data Warehouse Architect.

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TensorFlow 2 시작하기

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