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Google Cloud Training
本课程向您介绍 Transformer 架构和 Bidirectional Encoder Representations from Transformers (BERT) 模型。您将了解 Transformer 架构的主要组成部分，例如自注意力机制，以及该架构如何用于构建 BERT 模型。您还将了解可以使用 BERT 的不同任务，例如文本分类、问答和自然语言推理。完成本课程估计需要大约 45 分钟。
Register for this course and see more details by visiting:
OpenCourser.com/course/3xadaa/transformer
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What's inside
Syllabus
Transformer 模型和 BERT 模型：概览
在本单元中，您将了解 Transformer 架构的主要组成部分，例如自注意力机制，以及该架构如何用于构建 BERT 模型。您还将了解可以使用 BERT 的不同任务，例如文本分类、问答和自然语言推理。
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines Transformer models and BERT, and their uses in text classification, Q&A, and natural language inference, which are central to NLP
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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 Transformer Models and BERT Model - 简体中文 with these
activities:
Seek mentorship from NLP experts
Show steps
Connecting with NLP experts can provide valuable guidance and support for your learning journey.
Browse courses on
Natural Language Processing
Show steps
-
Identify potential mentors in the NLP field.
-
Reach out to them and express your interest in mentorship.
-
Attend meetings or discussions with your mentor.
Create a summary of course materials
Show steps
Reinforce your understanding by summarizing key concepts and ideas from the course materials.
Show steps
-
Review the lecture notes, readings, and other course materials.
-
Identify the main points and summarize them in your own words.
-
Organize your summary into a logical structure.
总结笔记和复习材料
Show steps
通过整理笔记和复习材料，加强对课程内容的理解和记忆。
Show steps
-
整理讲座笔记和学习材料
-
识别关键概念和要点
-
创建综合性复习材料
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Review natural language processing (NLP) concepts
Show steps
Refresh your understanding of NLP concepts to enhance your comprehension of Transformer and BERT models.
Browse courses on
Natural Language Processing
Show steps
-
Go through your previous NLP course materials.
-
Read articles or watch videos on NLP topics.
Review Transformer architecture tutorials
Show steps
Help you understand the fundamental concepts of Transformer and BERT models.
Browse courses on
Transformer Architecture
Show steps
-
Find online tutorials on Transformer architecture.
-
Watch the tutorials and take notes on the key concepts.
-
Practice implementing a simple Transformer model using a programming language.
讨论 BERT 模型在自然语言处理中的应用
Show steps
通过与同学讨论，开阔视野，了解 BERT 模型在自然语言处理领域的广泛应用。
Browse courses on
BERT
Show steps
-
收集 BERT 模型在自然语言处理中的应用实例
-
与同学分享并讨论发现
Complete BERT model training exercises
Show steps
Provide you with hands-on experience in training and evaluating BERT models.
Browse courses on
Natural Language Processing
Show steps
-
Download a pre-trained BERT model.
-
Fine-tune the model on a specific task, such as text classification or question answering.
-
Evaluate the performance of the fine-tuned model.
练习使用 BERT 进行文本分类
Show steps
通过实践提高使用 BERT 进行文本分类的技能，巩固对 BERT 模型的理解。
Browse courses on
BERT
Show steps
-
收集文本分类数据集
-
选择并使用合适的 BERT 模型
-
训练和评估 BERT 模型
构建 BERT 模型并应用于文本分类任务
Show steps
通过实际动手构建可用于文本分类的 BERT 模型，掌握 BERT 模型的应用实践，巩固学习成果。
Browse courses on
BERT
Show steps
-
收集和预处理文本分类数据集
-
选择并加载合适的 BERT 模型
-
微调 BERT 模型
-
评估模型在文本分类任务上的性能
Contribute to open-source NLP projects
Show steps
Practical experience through open-source contributions can deepen your understanding of BERT models and NLP.
Browse courses on
Natural Language Processing
Show steps
-
Find open-source NLP projects on platforms like GitHub.
-
Identify areas where you can contribute your skills.
-
Submit pull requests or participate in discussions.
Seek mentorship from NLP experts
Show steps
Connecting with NLP experts can provide valuable guidance and support for your learning journey.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Identify potential mentors in the NLP field.
- Reach out to them and express your interest in mentorship.
- Attend meetings or discussions with your mentor.
Create a summary of course materials
Show steps
Reinforce your understanding by summarizing key concepts and ideas from the course materials.
Show steps
Show steps
Show steps
- Review the lecture notes, readings, and other course materials.
- Identify the main points and summarize them in your own words.
- Organize your summary into a logical structure.
总结笔记和复习材料
Show steps
通过整理笔记和复习材料，加强对课程内容的理解和记忆。
Show steps
Show steps
Show steps
- 整理讲座笔记和学习材料
- 识别关键概念和要点
- 创建综合性复习材料
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Review natural language processing (NLP) concepts
Show steps
Refresh your understanding of NLP concepts to enhance your comprehension of Transformer and BERT models.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Go through your previous NLP course materials.
- Read articles or watch videos on NLP topics.
Review Transformer architecture tutorials
Show steps
Help you understand the fundamental concepts of Transformer and BERT models.
Browse courses on
Transformer Architecture
Show steps
Show steps
Show steps
- Find online tutorials on Transformer architecture.
- Watch the tutorials and take notes on the key concepts.
- Practice implementing a simple Transformer model using a programming language.
讨论 BERT 模型在自然语言处理中的应用
Show steps
通过与同学讨论，开阔视野，了解 BERT 模型在自然语言处理领域的广泛应用。
Browse courses on
BERT
Show steps
Show steps
Show steps
- 收集 BERT 模型在自然语言处理中的应用实例
- 与同学分享并讨论发现
Complete BERT model training exercises
Show steps
Provide you with hands-on experience in training and evaluating BERT models.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Download a pre-trained BERT model.
- Fine-tune the model on a specific task, such as text classification or question answering.
- Evaluate the performance of the fine-tuned model.
练习使用 BERT 进行文本分类
Show steps
通过实践提高使用 BERT 进行文本分类的技能，巩固对 BERT 模型的理解。
Browse courses on
BERT
Show steps
Show steps
Show steps
- 收集文本分类数据集
- 选择并使用合适的 BERT 模型
- 训练和评估 BERT 模型
构建 BERT 模型并应用于文本分类任务
Show steps
通过实际动手构建可用于文本分类的 BERT 模型，掌握 BERT 模型的应用实践，巩固学习成果。
Browse courses on
BERT
Show steps
Show steps
Show steps
- 收集和预处理文本分类数据集
- 选择并加载合适的 BERT 模型
- 微调 BERT 模型
- 评估模型在文本分类任务上的性能
Contribute to open-source NLP projects
Show steps
Practical experience through open-source contributions can deepen your understanding of BERT models and NLP.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find open-source NLP projects on platforms like GitHub.
- Identify areas where you can contribute your skills.
- Submit pull requests or participate in discussions.
Career center
Learners who complete Transformer Models and BERT Model - 简体中文 will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists analyze data to create algorithms that machine learning depends on. A background in Transformer and BERT would be a perfect fit for this world. Transformer Models are used for generating images, doing language translation, and building chatbots. This course would give a boost to someone looking to become a Data Scientist.
Natural Language Processing Engineer
Natural Language Processing Engineer
NLP Engineers design algorithms that help computers understand and extract meaning from human language. This course covers the Bidirectional Encoder Representations from Transformers (BERT) model, a cornerstone in NLP engineering. This course would be helpful for someone who wants to work as an NLP Engineer.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, deploy, and maintain the models that do the machine learning. Transformer Models are crucial to ML. The BERT model is often used in the field. This course would be helpful for someone who wants to become an MLE.
Data Analyst
Data Analyst
Data Analysts collect and interpret data in order to make recommendations for their organization. A background in Transformer would be helpful for a DA who works with NLP.
Research Scientist
Research Scientist
Research Scientists design and conduct scientific experiments, then analyze results. The Transformer Architecture is at the heart of many scientific innovations. For anyone working on a team that uses Transformer, this course may be helpful.
Business Analyst
Business Analyst
Business Analysts analyze and solve business problems. BAs who work with NLP may find this course helpful, because of its focus on BERT, a popular NLP model.
Information Architect
Information Architect
Information Architects design and maintain the structure and organization of websites and other digital information systems. IAs who work with NLP may find this course helpful. It covers the BERT model, which is a cornerstone of NLP.
Technical Writer
Technical Writer
Technical Writers explain complex technical information to non-technical people. TWs who are writing about NLP may find this helpful. It covers the BERT model, which is a fundamental part of NLP.
Software Engineer
Software Engineer
Software Engineers design, develop and maintain computer applications. Many SEs work with NLP. For an SE who wants to work with NLP, this course may be helpful.
Content Strategist
Content Strategist
Content Strategists plan and oversee the creation and distribution of content. Some CSs work with NLP. This course may be helpful for such CSs.
Interaction Designer
Interaction Designer
Interaction Designers create the interactive elements of websites and apps. For IxD working on an NLP-driven product, this course may be helpful.
Data Engineer
Data Engineer
Data Engineers build and maintain the systems that store and process data. Some DSEs specialize in NLP, so this course may be helpful for someone pursuing that.
Digital Marketing Manager
Digital Marketing Manager
Digital Marketing Managers plan and execute marketing campaigns online. A background in NLP may be helpful for a DM who is working on campaigns in the NLP space.
User Experience Designer
User Experience Designer
User Experience Designers research and design website and app interfaces so that they are easy and enjoyable to use. If a UX Designer is working on an NLP product, this course may be helpful.
Product Manager
Product Manager
Product Managers lead teams that develop and maintain software products. PMs usually need a technical background in the product they are responsible for. If a PM is working with NLP, this course may be helpful.
For more career information including salaries, visit:
OpenCourser.com/course/3xadaa/transformer
Reading list
We've selected seven 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 - 简体中文.
这本书提供了自然语言处理中深度学习的综合介绍。它涵盖了各种模型和技术，包括 Transformer 模型。虽然这本书不专门针对 Transformer 模型，但它为读者提供了 NLP 中深度学习的基础知识，这对于理解 Transformer 模型至关重要。
这本书提供了机器学习中使用的数学基础的全面介绍。虽然这本书不专门针对 Transformer 模型，但它为读者提供了数学基础，这对于理解 Transformer 模型至关重要。
这本书提供了语音和语言处理的全面介绍。虽然这本书不专门针对 Transformer 模型，但它为读者提供了语音和语言处理的基础知识，这对于理解 Transformer 模型至关重要。
这本书提供了信息论、推理和学习算法的全面介绍。虽然这本书不专门针对 Transformer 模型，但它为读者提供了信息论和学习算法的基础知识，这对于理解 Transformer 模型至关重要。
这本书提供了凸优化的全面介绍。虽然这本书不专门针对 Transformer 模型，但它为读者提供了凸优化的基础知识，这对于理解 Transformer 模型至关重要。
Save
这本书提供了深度学习的全面介绍。虽然这本书不专门针对 Transformer 模型，但它为读者提供了深度学习的基础知识，这对于理解 Transformer 模型至关重要。
Save
这本书提供了机器学习的全面介绍。虽然这本书不专门针对 Transformer 模型，但它为读者提供了机器学习的基础知识，这对于理解 Transformer 模型至关重要。
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3xadaa/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
Examines Transformer models and BERT, and their uses in text classification, Q&A, and natural language inference, which are central to NLP
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