Transformer Models and BERT Model
This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference. This course is estimated to take approximately 45 minutes to complete.
Monthly Subscription Starting at AED 99 + VAT
- Level Expert
- Duration 1 hour
- Course by Google Cloud
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About
This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference. This course is estimated to take approximately 45 minutes to complete.Modules
Untitled Lesson
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2
Videos
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1
Readings
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1
Assignment
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Assignment
- Transformer Models and BERT Model: Quiz
2
Videos
- Transformer Models and BERT Model: Overview
- Transformer Models and BERT Model: Lab Walkthrough
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Readings
- Transformer Models and BERT Model: Lab Resources
Auto Summary
Explore the fascinating world of Transformer architecture and the BERT model with this expert-level course offered by Coursera. Dive into the intricacies of the self-attention mechanism and discover how it forms the backbone of the powerful BERT model. You'll gain a thorough understanding of how BERT can be applied to various tasks, including text classification, question answering, and natural language inference. Designed for those with advanced knowledge in IT and Computer Science, this concise 45-minute course provides a focused and efficient learning experience. Available through a Starter subscription, this course is ideal for professionals looking to deepen their expertise in cutting-edge natural language processing technologies.
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