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這堂課程將說明變換器架構，以及基於變換器的雙向編碼器表示技術 (BERT) 模型，同時帶您瞭解變換器架構的主要組成 (如自我注意力機制) 和如何用架構建立 BERT 模型。此外，也會介紹 BERT 適用的各種任務，像是文字分類、問題回答和自然語言推論。課程預計約 45 分鐘。
Register for this course and see more details by visiting:
OpenCourser.com/course/vicf3m/transformer
What's inside
Syllabus
變換器模型與 BERT 模型：總覽
在這個單元中，您可以瞭解變換器架構的主要組成 (如自我注意力機制) 和如何用架構建立 BERT 模型，同時認識 BERT 適用的各種任務，像是文字分類、問題回答和自然語言推論。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops fluency in transformer models, encompassing BERT, which is popular in natural language processing research and industry
Introduces BERT tasks like text classification, question answering, and natural language inference, offering practical applications of the model
Delivered by Google Cloud Training, implying industry relevance and expertise in the field
Suitable for beginners who wish to gain a foundational understanding of transformer models and their applications
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
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it. Supplement your coursework and achieve mastery of the topics covered
in Transformer Models and BERT Model - 繁體中文 with these
activities:
組織學習資料
Show steps
整理課程筆記、作業和考試，建立有條理的學習資料夾，加強學習效率。
Show steps
-
建立筆記、作業和考試資料夾
-
定期整理和更新學習資料
-
建立知識清單或目錄
深入了解 BERT 架構
Show steps
透過觀看教程，熟悉 BERT 架構的組成和運作原理，建立對模型的深入理解。
Show steps
-
觀看 Coursera 提供的 BERT 教學影片
-
閱讀 Google AI Blog 上關於 BERT 的文章
-
瀏覽有關 Transformer 模型的技術文件
Show all two activities
組織學習資料
Show steps
整理課程筆記、作業和考試，建立有條理的學習資料夾，加強學習效率。
Show steps
Show steps
Show steps
- 建立筆記、作業和考試資料夾
- 定期整理和更新學習資料
- 建立知識清單或目錄
深入了解 BERT 架構
Show steps
透過觀看教程，熟悉 BERT 架構的組成和運作原理，建立對模型的深入理解。
Show steps
Show steps
Show steps
- 觀看 Coursera 提供的 BERT 教學影片
- 閱讀 Google AI Blog 上關於 BERT 的文章
- 瀏覽有關 Transformer 模型的技術文件
Show all two activities
Career center
Learners who complete Transformer Models and BERT Model - 繁體中文 will develop knowledge and skills
that may be useful to these careers:
Computational Linguist
Computational Linguist
Computational Linguists apply computational techniques to study and analyze language. This course on Transformer Models and BERT Model is highly relevant to Computational Linguists as it delves into the theoretical foundations and practical applications of transformer models, which have revolutionized NLP and are used in a wide range of computational linguistics tasks. By gaining a deep understanding of transformer models, learners can enhance their ability to develop and apply computational techniques to advance the field of linguistics.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers specialize in developing and applying techniques to enable computers to understand and generate human language. This course on Transformer Models and BERT Model provides a comprehensive overview of transformer models, which have revolutionized NLP and are used in a wide range of applications, including machine translation, text summarization, and question answering. By gaining a deep understanding of transformer models and their capabilities, learners can enhance their ability to design and implement NLP solutions that effectively handle complex language-related tasks.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models to solve real-world problems. This course on Transformer Models and BERT Model can be particularly beneficial for Machine Learning Engineers as it delves into the technical details of transformer models, which are widely used in NLP applications. By learning about the architecture, components, and training techniques of transformer models, learners can gain valuable knowledge and skills that are directly applicable to their role in developing and implementing NLP solutions.
Data Scientist
Data Scientist
Data Scientists apply mathematics and statistics to extract knowledge and insights from data using complex machine learning models, and they are in high demand in various industries such as technology, healthcare, and finance. This course on Transformer Models and BERT Model provides a strong foundation for understanding the inner workings of transformer models, which are a powerful class of neural network architectures used in natural language processing (NLP). By gaining a deep understanding of transformer models and their applications, learners can enhance their abilities to develop, train, and evaluate machine learning models for NLP tasks, a critical skill for Data Scientists.
Research Scientist
Research Scientist
Research Scientists conduct research to advance scientific knowledge and develop new technologies. This course on Transformer Models and BERT Model can be valuable for Research Scientists working in NLP or related fields, as it provides in-depth knowledge of transformer models, a key technology in NLP research. By understanding the theoretical foundations, strengths, and limitations of transformer models, learners can contribute to the development of novel NLP techniques and applications.
Linguist
Linguist
Linguists study the structure and meaning of language. This course on Transformer Models and BERT Model may be helpful for Linguists who specialize in computational linguistics or related fields, as it provides a comprehensive overview of transformer models, a key technology in NLP. By gaining a deep understanding of transformer models, learners can enhance their ability to analyze and interpret language data using computational techniques.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to provide insights for decision-making. This course on Transformer Models and BERT Model may be beneficial for Data Analysts who work with NLP data, as it provides a foundation for understanding transformer models, a powerful technique for NLP tasks. By gaining familiarity with transformer models, learners can improve their ability to extract meaningful insights from NLP data and contribute to data-driven decision-making.
Speech Scientist
Speech Scientist
Speech Scientists study the production and perception of speech. This course on Transformer Models and BERT Model may be useful for Speech Scientists who work on NLP-related projects, as transformer models are widely used in speech recognition and synthesis applications. By gaining proficiency in transformer models, learners can enhance their ability to develop and contribute to NLP solutions that improve speech technologies.
User Experience Designer
User Experience Designer
User Experience Designers create products and services that are easy to use and enjoyable. This course on Transformer Models and BERT Model may be useful for User Experience Designers who work on NLP-related projects, as transformer models are used in a wide range of applications, including chatbots, virtual assistants, and language translation tools. By gaining proficiency in transformer models, learners can enhance their ability to design and implement NLP solutions that provide a seamless and intuitive user experience.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course on Transformer Models and BERT Model may be helpful for Software Engineers working on NLP-related projects, as it provides a solid understanding of transformer models, which are widely used in NLP applications. By gaining proficiency in transformer models, learners can enhance their ability to develop and contribute to NLP software solutions.
Information Architect
Information Architect
Information Architects design and organize information systems to make them easy to find and use. This course on Transformer Models and BERT Model may be useful for Information Architects who work on NLP-related projects, as transformer models are used in a wide range of applications, including search engines, recommendation systems, and chatbots. By gaining proficiency in transformer models, learners can enhance their ability to design and implement NLP solutions that effectively meet the needs of users.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course on Transformer Models and BERT Model may be beneficial for Quantitative Analysts who work with NLP data, as it provides a foundation for understanding transformer models, a powerful technique for NLP tasks. By gaining familiarity with transformer models, learners can improve their ability to extract meaningful insights from NLP data and make data-driven investment decisions.
Technical Writer
Technical Writer
Technical Writers create documentation and other materials to explain complex technical information. This course on Transformer Models and BERT Model may be helpful for Technical Writers who specialize in NLP or related fields, as it provides a comprehensive overview of transformer models, a key technology in NLP. By gaining a deep understanding of transformer models, learners can enhance their ability to accurately and effectively communicate technical concepts related to NLP to a wide range of audiences.
Business Analyst
Business Analyst
Business Analysts help organizations improve their performance by analyzing business processes and identifying areas for improvement. This course on Transformer Models and BERT Model may be useful for Business Analysts who work in industries that rely heavily on NLP, such as marketing, customer service, or finance. By understanding the capabilities of transformer models, learners can gain insights into how NLP can be leveraged to improve business processes and enhance customer experiences.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products or features. This course on Transformer Models and BERT Model may be useful for Product Managers who work on NLP-related products, as it provides insights into the capabilities and limitations of transformer models, a core technology in NLP. By understanding transformer models, learners can make informed decisions about product design and prioritize features that leverage NLP effectively.
For more career information including salaries, visit:
OpenCourser.com/course/vicf3m/transformer
Reading list
We've selected four 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
Transformer Models and BERT Model - 繁體中文.
這篇文章提供 BERT 模型的詳細解釋，涵蓋其架構、訓練方法和效能，適合對 BERT 模型有深入了解的讀者。
這本書是自然語言處理領域的教科書，全面介紹自然語言處理的各種技術。
這本書提供了自然語言處理的人工智慧指南，包括 BERT 模型。適合有自然語言處理和人工智慧基礎的讀者深入了解 BERT 模型的理論原理和應用。
這本書提供 PyTorch 中變換器模型的實作範例，涵蓋各種自然語言處理任務，適合對變換器模型和 PyTorch 有興趣的開發人員和工程師。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/vicf3m/transformer
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Effort
1 week of study, 6-8 hours
Level
Advanced
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
中文
Transcript
English
Good to know
Develops fluency in transformer models, encompassing BERT, which is popular in natural language processing research and industry
Introduces BERT tasks like text classification, question answering, and natural language inference, offering practical applications of the model
Delivered by Google Cloud Training, implying industry relevance and expertise in the field
Suitable for beginners who wish to gain a foundational understanding of transformer models and their applications
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