We may earn an affiliate commission when you visit our partners.
Google Cloud Training
이 과정은 Transformer 아키텍처와 BERT(Bidirectional Encoder Representations from Transformers) 모델을 소개합니다. 셀프 어텐션 메커니즘 같은 Transformer 아키텍처의 주요 구성요소와 이 아키텍처가 BERT 모델 빌드에 사용되는 방식에 관해 알아봅니다. 또한 텍스트 분류, 질문 답변, 자연어 추론과 같이 BERT를 활용할 수 있는 다양한 작업에 대해서도 알아봅니다. 이 과정은 완료하는 데 대략 45분이 소요됩니다.
Register for this course and see more details by visiting:
OpenCourser.com/course/jev9i5/transformer
Three deals to help you save
We found three deals and offers that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until December 12
Annual Subscription Savings
Unlock programs from Google, Microsoft, and IBM and join 77% of learners who reported positive career outcomes.
Only $239!
Valid for a limited time only
Future-proof your career
Access O'Reilly books, live events, courses, and more. Save with an annual subscription.
Take
15%
off
What's inside
Syllabus
Transformer 모델 및 BERT 모델: 개요
이 모듈에서는 셀프 어텐션 메커니즘 같은 Transformer 아키텍처의 주요 구성요소와 이 아키텍처가 BERT 모델 빌드에 사용되는 방식에 대해 알아봅니다. 또한 텍스트 분류, 질문 답변, 자연어 추론과 같이 BERT를 활용할 수 있는 다양한 작업에 대해서도 알아봅니다.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores Transformer architecture and BERT model, which are industry-standard natural language processing architectures
Taught by Google Cloud Training, which is recognized for its expertise in cloud computing and artificial intelligence
Develops skills in text classification, question answering, and natural language inference, which are core skills for data scientists and NLP engineers
Save this course
Save Transformer Models and BERT Model - 한국어 to your list so you can find it easily later:
Save
Save
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 - 한국어 with these
activities:
Review core components of Transformer
Show steps
Reviewing the core components of Transformer, such as the attention mechanism, will strengthen your understanding of the foundations of BERT.
Show steps
-
Revisit materials on self-attention and multi-head attention mechanisms.
-
Go through the encoder and decoder architecture of Transformer.
-
Practice implementing a simple Transformer model with self-attention.
Work through BERT tutorials
Show steps
Hands-on tutorials will provide you with practical experience in working with BERT models.
Browse courses on
BERT Model
Show steps
-
Find introductory tutorials on BERT.
-
Follow a tutorial that walks through building a BERT model from scratch.
-
Experiment with different BERT hyperparameters and observe their impact on model performance.
Solve BERT exercises and tasks
Show steps
Solving exercises and completing tasks specifically designed for BERT will help you refine your understanding and improve your problem-solving skills.
Browse courses on
Natural Language Processing
Show steps
-
Find online platforms or resources that offer BERT exercises.
-
Attempt to solve a variety of exercises covering different aspects of BERT.
-
Participate in online competitions or hackathons focused on BERT.
Two other activities
Expand to see all activities and additional details
Show all five activities
Assist fellow learners with BERT-related questions
Show steps
Mentoring others will reinforce your understanding of BERT and enhance your ability to communicate complex concepts.
Browse courses on
Peer Support
Show steps
-
Join online forums or discussion groups related to BERT.
-
Actively participate in discussions and answer questions from fellow learners.
-
Organize study sessions or workshops to share your knowledge and collaborate with others.
Build a mini-project using BERT
Show steps
Building a mini-project using BERT will allow you to apply your knowledge in a practical setting and gain valuable experience.
Browse courses on
Text Classification
Show steps
-
Identify a specific task or problem that you can address with BERT.
-
Gather and prepare the necessary data for your project.
-
Design and implement your BERT model.
-
Evaluate the performance of your model and make improvements as needed.
-
Present your project and findings.
Review core components of Transformer
Show steps
Reviewing the core components of Transformer, such as the attention mechanism, will strengthen your understanding of the foundations of BERT.
Show steps
Show steps
Show steps
- Revisit materials on self-attention and multi-head attention mechanisms.
- Go through the encoder and decoder architecture of Transformer.
- Practice implementing a simple Transformer model with self-attention.
Work through BERT tutorials
Show steps
Hands-on tutorials will provide you with practical experience in working with BERT models.
Browse courses on
BERT Model
Show steps
Show steps
Show steps
- Find introductory tutorials on BERT.
- Follow a tutorial that walks through building a BERT model from scratch.
- Experiment with different BERT hyperparameters and observe their impact on model performance.
Solve BERT exercises and tasks
Show steps
Solving exercises and completing tasks specifically designed for BERT will help you refine your understanding and improve your problem-solving skills.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Find online platforms or resources that offer BERT exercises.
- Attempt to solve a variety of exercises covering different aspects of BERT.
- Participate in online competitions or hackathons focused on BERT.
Two other activities
Expand to see all activities and additional details
Show all five activities
Assist fellow learners with BERT-related questions
Show steps
Mentoring others will reinforce your understanding of BERT and enhance your ability to communicate complex concepts.
Browse courses on
Peer Support
Show steps
Show steps
Show steps
- Join online forums or discussion groups related to BERT.
- Actively participate in discussions and answer questions from fellow learners.
- Organize study sessions or workshops to share your knowledge and collaborate with others.
Build a mini-project using BERT
Show steps
Building a mini-project using BERT will allow you to apply your knowledge in a practical setting and gain valuable experience.
Browse courses on
Text Classification
Show steps
Show steps
Show steps
- Identify a specific task or problem that you can address with BERT.
- Gather and prepare the necessary data for your project.
- Design and implement your BERT model.
- Evaluate the performance of your model and make improvements as needed.
- Present your project and findings.
Career center
Learners who complete Transformer Models and BERT Model - 한국어 will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers work with machine learning models to enable computers to understand and interpret human language. This course can help build a foundation for this career by introducing the concepts behind BERT and Transformer models, which are essential for building NLP models. These models are used in a wide variety of NLP tasks, such as machine translation, text summarization, and question answering.
Computational Linguist
Computational Linguist
Computational Linguists study the intersection of computer science and linguistics. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which are important for understanding natural language processing. These models are used in a wide variety of computational linguistics tasks, such as machine translation, text summarization, and question answering.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the natural language processing capabilities of software systems. These models can be used to make it easier for software systems to understand and interpret user input.
Data Scientist
Data Scientist
Data Scientists use machine learning to improve business processes. This course can help build a foundation for this career by introducing Transformer models and BERT models, which are crucial components of NLP, an essential field in data science. This model is vital for processing and extracting data from unstructured text, which forms a large part of the big data used in modern business.
Product Manager
Product Manager
Product Managers manage the development and launch of new products. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the natural language processing capabilities of products. These models can be used to make it easier for users to interact with products and to get the most out of them.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers work with data scientists to implement the models that data scientists create. This course can build a foundation for this career by introducing the concepts behind BERT and Transformer models, which are important for understanding and building large language models. These models are used in a wide variety of machine learning tasks, such as natural language processing, computer vision, and speech recognition.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make better decisions. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the accuracy and efficiency of data analysis. These models can be used to extract insights from data that would be difficult or impossible to find using traditional methods.
User Experience Designer
User Experience Designer
User Experience Designers design and evaluate the user experience of websites and other digital products. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the natural language processing capabilities of digital products. These models can be used to make it easier for users to interact with digital products.
Information Architect
Information Architect
Information Architects design and organize websites and other information systems. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the search functionality of websites. These models can be used to make it easier for users to find the information they are looking for.
Customer Success Manager
Customer Success Manager
Customer Success Managers help customers get the most out of their products and services. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the customer experience. These models can be used to identify and resolve customer issues, develop customer training programs, and measure customer satisfaction.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns to promote products and services. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the effectiveness of marketing campaigns. These models can be used to identify and target potential customers, develop marketing messages, and measure the impact of marketing campaigns.
Technical Writer
Technical Writer
Technical Writers create documentation for software and other technical products. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to generate natural language text. These models can be used to create documentation that is more accurate, clear, and concise.
Sales Manager
Sales Manager
Sales Managers lead and motivate sales teams to achieve sales goals. This course can help build a foundation for this career by introducing the concepts behind Transformer models and BERT models, which can be used to improve the effectiveness of sales teams. These models can be used to identify and qualify leads, develop sales pitches, and close deals.
Lexicographer
Lexicographer
Lexicographers research and compile dictionaries. This course may be useful for Lexicographers because it introduces the concepts behind Transformer models and BERT models, which can be used to analyze and understand the semantics of words and phrases. These models can be used to improve the accuracy and completeness of dictionaries.
Business Analyst
Business Analyst
Business Analysts help businesses understand their needs and develop solutions to meet those needs. This course may be useful for Business Analysts because it introduces the concepts behind Transformer models and BERT models, which can be used to improve the accuracy and efficiency of business analysis. These models can be used to identify and prioritize business requirements, develop business cases, and evaluate the impact of business decisions.
For more career information including salaries, visit:
OpenCourser.com/course/jev9i5/transformer
Reading list
We've selected six 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 - 한국어.
Provides a comprehensive overview of deep learning methods for natural language processing. It valuable resource for anyone interested in learning more about the latest developments in NLP.
Provides a practical guide to using PyTorch for natural language processing tasks. It valuable resource for anyone interested in implementing NLP models using PyTorch.
Provides a comprehensive overview of the NLTK library for natural language processing. It valuable resource for anyone interested in learning more about NLP and using NLTK for NLP tasks.
Save
Provides a comprehensive overview of text mining techniques using R. It valuable resource for anyone interested in learning more about text mining and using R for text mining tasks.
Save
Provides a comprehensive overview of machine learning methods for text. It valuable resource for anyone interested in learning more about NLP and using machine learning for NLP tasks.
Save
Provides a practical guide to building and deploying NLP models using transformers, with a focus on the TensorFlow ecosystem.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jev9i5/transformer
Share
Similar courses
Here are nine courses similar to
Transformer Models and BERT Model - 한국어.
Gemini in Google Docs - 한국어
OpenCourser.com/course/5d4fxp/gemini
Gemini in Google Docs - 한국어
Most relevant
Encoder-Decoder Architecture - 한국어
OpenCourser.com/course/tiu4qc/encoder
Encoder-Decoder Architecture - 한국어
Most relevant
Feature Engineering - 한국어
OpenCourser.com/course/m77ew9/feature
Feature Engineering - 한국어
Most relevant
Essential Cloud Infrastructure: Foundation - 한국어
OpenCourser.com/course/1qxicg/essential
Essential Cloud Infrastructure: Foundation - 한국어
Most relevant
Transformer Models and BERT Model
OpenCourser.com/course/24z5l2/transformer
Transformer Models and BERT Model
Transformer Models and BERT Model - Bahasa Indonesia
OpenCourser.com/course/h1ptq0/transformer
Transformer Models and BERT Model - Bahasa Indonesia
Transformer Models and BERT Model with Google Cloud
OpenCourser.com/course/c2x4xz/transformer
Transformer Models and BERT Model with Google Cloud
Python에서 데이터베이스 사용하기
OpenCourser.com/course/xtfwdg/pythoneseo
Python에서 데이터베이스 사용하기
Transformer Models and BERT Model - Français
OpenCourser.com/course/av9waq/transformer
Transformer Models and BERT Model - Français
Effort
1 week of study, 6-8 hours
Level
Advanced
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
한국어
Transcript
English
Good to know
Explores Transformer architecture and BERT model, which are industry-standard natural language processing architectures
Taught by Google Cloud Training, which is recognized for its expertise in cloud computing and artificial intelligence
Develops skills in text classification, question answering, and natural language inference, which are core skills for data scientists and NLP engineers
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser