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September 4, 2024
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Instructor: Google Cloud Training
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(105 reviews)
(105 reviews)
Understand the main components of the Transformer architecture.
Learn how a BERT model is built using Transformers.
Use BERT to solve different natural language processing (NLP) tasks.
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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.
In this module you will 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.
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105 reviews
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Reviewed on Mar 12, 2024
Excellent and concise presentation of Transformer and BERT models. The course designer may consider adding programming assignments to illustrate the concepts and to reinforce student learning.
Reviewed on Jun 24, 2023
very clear and detailed explanation of the transformers with practical example of training BERT model
Reviewed on Jul 16, 2023
course was amazing gave me a good overview of BERT model and concepts like Encoding and decoding but not for beginner :>
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