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이 과정은 기계 번역, 텍스트 요약, 질의 응답과 같은 시퀀스-투-시퀀스(Seq2Seq) 작업에 널리 사용되는 강력한 머신러닝 아키텍처인 인코더-디코더 아키텍처에 대한 개요를 제공합니다. 인코더-디코더 아키텍처의 기본 구성요소와 이러한 모델의 학습 및 서빙 방법에 대해 알아봅니다. 해당하는 실습 둘러보기에서는 TensorFlow에서 시를 짓는 인코더-디코더 아키텍처를 처음부터 간단하게 구현하는 코딩을 해봅니다.
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What's inside
Syllabus
인코더-디코더 아키텍처: 개요
이 모듈은 기계 번역, 텍스트 요약, 질의 응답과 같은 시퀀스-투-시퀀스(Seq2Seq) 작업에 널리 사용되는 강력한 머신러닝 아키텍처인 인코더-디코더 아키텍처에 대한 개요를 제공합니다. 인코더-디코더 아키텍처의 기본 구성요소와 이러한 모델의 학습 및 서빙 방법에 대해 알아봅니다. 해당하는 실습 둘러보기에서는 TensorFlow에서 시를 짓는 인코더-디코더 아키텍처를 처음부터 간단하게 구현하는 코딩을 해봅니다.
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possible dealbreakers
Useful For those interested in machine learning and natural language processing
Introduces the basics of encoder-decoder architecture
Taught by Google Cloud Training
Hands-on coding exercise to build an encoder-decoder architecture
May require prerequisite knowledge in machine learning
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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 Encoder-Decoder Architecture - 한국어 with these
activities:
Review tensor basics
Show steps
Sharpen your basic understanding of tensor manipulation to prepare for the complexities of encoder-decoder architectures.
Show steps
-
Revisit tensor creation and operations
-
Practice common tensor operations like slicing, indexing, and broadcasting
Encoder-Decoder アーキテクチャのコーディング演習
Show steps
このアクティビティは、実践的なコーディングの経験を通じて、学習を強化します。
Browse courses on
TensorFlow
Show steps
-
TensorFlow で単純な Encoder-Decoder アーキテクチャを実装する
-
モデルのトレーニングと評価を実行する
-
詩を生成するタスクに対するモデルのテスト
Show all two activities
Review tensor basics
Show steps
Sharpen your basic understanding of tensor manipulation to prepare for the complexities of encoder-decoder architectures.
Show steps
Show steps
Show steps
- Revisit tensor creation and operations
- Practice common tensor operations like slicing, indexing, and broadcasting
Encoder-Decoder アーキテクチャのコーディング演習
Show steps
このアクティビティは、実践的なコーディングの経験を通じて、学習を強化します。
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- TensorFlow で単純な Encoder-Decoder アーキテクチャを実装する
- モデルのトレーニングと評価を実行する
- 詩を生成するタスクに対するモデルのテスト
Show all two activities
Career center
Learners who complete Encoder-Decoder Architecture - 한국어 will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer builds and maintains machine learning models, which are used to make predictions or decisions based on data. This role requires a strong foundation in computer science and machine learning techniques, including the concepts of this course, which teaches foundational elements of machine learning.
Research Scientist
Research Scientist
A Research Scientist conducts research in a particular field of science or engineering. Many Research Scientists specialize in machine learning, which is a subfield of computer science that deals with teaching computers to learn from data. This course may be helpful in getting started in machine learning research.
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer designs and develops systems that enable computers to understand and generate human language. This course may be helpful as it covers the foundational concepts of machine learning, which is heavily used in natural language processing.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to solve complex problems in business and industry. This course may be helpful for you as an Operations Research Analyst as it delves into the fundamentals of machine learning techniques, which have become increasingly popular for solving complex problems.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains the infrastructure that stores and processes data. This course may be helpful for you as a Data Engineer as it delves into the fundamentals of machine learning techniques, which can be used to process data.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, interprets, and presents data. This course may be helpful for you as a Data Analyst as it delves into the fundamentals of machine learning techniques, which are often used to analyze and interpret data.
Statistician
Statistician
A Statistician collects, analyzes, interprets, and presents data. This course may be helpful for you as a Statistician as it delves into the fundamentals of machine learning techniques, which can be used to analyze and interpret data.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze data and make predictions. This course, which focuses on the core principles of machine learning, may be helpful as machine learning is becoming increasingly important in the field of quantitative analysis.
Actuary
Actuary
An Actuary uses mathematical and statistical models to assess and manage risk. This course may be helpful for you as an Actuary as it delves into the fundamentals of machine learning techniques, which are often used to assess and manage risk.
Financial Analyst
Financial Analyst
A Financial Analyst uses financial data to make investment recommendations. This course, which covers foundational elements of machine learning, may be helpful for you in a career as a Financial Analyst, as machine learning is becoming increasingly integrated with financial analysis.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course, which focuses on teaching the core principles of machine learning, could help you build a foundation for a role as a Software Engineer, as machine learning is becoming increasingly integrated with software development.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. This course may be helpful for you as a Product Manager as it covers the fundamentals of machine learning, which is becoming increasingly used to improve product development and marketing.
Software Developer
Software Developer
A Software Developer designs, develops, and maintains software applications. This course, which focuses on teaching the core principles of machine learning, could help you build a foundation for a role as a Software Developer, as machine learning is becoming increasingly integrated with software development.
Data Scientist
Data Scientist
A Data Scientist uses scientific methods to extract insights from data. This often helps organizations make decisions about everything from marketing campaigns to product development. Since the field of data science is heavily reliant upon machine learning, this course, which focuses on teaching the core principles of machine learning, may be helpful in supplementing your skills for a career as a Data Scientist.
Business Analyst
Business Analyst
A Business Analyst uses data to help businesses make better decisions. This course, which teaches the fundamentals of machine learning, may be helpful as machine learning can be used to analyze data and identify trends that can help businesses make better decisions.
For more career information including salaries, visit:
OpenCourser.com/course/tiu4qc/encoder
Reading list
We've selected 13 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
Encoder-Decoder Architecture - 한국어.
Provides a comprehensive overview of computational linguistics and natural language processing. It covers a wide range of topics, including morphology, syntax, semantics, and pragmatics.
Save
딥러닝 아키텍처와 알고리즘에 대해 자세히 설명합니다. 인코더-디코더 아키텍처를 더 깊이 이해하는 데 도움이 될 수 있습니다.
Provides a comprehensive overview of statistical learning. It covers a wide range of topics, including linear regression, logistic regression, and decision trees.
Save
Provides a comprehensive overview of deep learning techniques for natural language processing. It covers a wide range of topics, including word embeddings, recurrent neural networks, and convolutional neural networks.
Provides a comprehensive overview of speech and language processing. It covers a wide range of topics, including acoustics, phonetics, phonology, and syntax.
Provides a practical introduction to machine learning using Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, including data preprocessing, feature engineering, and model evaluation.
Provides a practical introduction to natural language processing using Python. It covers a wide range of topics, including text preprocessing, feature extraction, and machine learning algorithms.
Provides a practical introduction to deep learning using Fastai and PyTorch. It covers a wide range of topics, including image classification, object detection, and natural language processing.
Provides a practical introduction to natural language processing using Python. It covers a wide range of topics, including text preprocessing, feature extraction, and machine learning algorithms.
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Provides a practical introduction to natural language processing using TensorFlow. It covers a wide range of topics, including text preprocessing, feature extraction, and machine learning algorithms.
Save
머신러닝의 기본 원리를 소개하고, 기계학습 알고리즘의 종류와 응용 분야를 다룹니다. 본 과정의 배경 지식을 제공하는 데 도움이 될 수 있습니다.
Save
인간의 언어와 인지 능력에 대한 기초 지식을 제공합니다. 인코더-디코더 아키텍처가 인간 언어를 이해하는 데 어떻게 사용되는지 이해하는 데 도움이 될 수 있습니다.
미적분학, 선형대수 및 통계학을 포함한 수학의 기본 개념을 소개합니다. 인코더-디코더 아키텍처에서 사용되는 수학적 원리를 이해하는 데 도움이 될 수 있습니다.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/tiu4qc/encoder
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Level
Advanced
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
한국어
Transcript
English
Good to know
Useful For those interested in machine learning and natural language processing
Introduces the basics of encoder-decoder architecture
Taught by Google Cloud Training
Hands-on coding exercise to build an encoder-decoder architecture
May require prerequisite knowledge in machine learning
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