What Is an NFT? Your Guide to Non-Fungible Tokens in 2025
January 6, 2025
Article · 7 min read
Instructor: Google Cloud Training
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(94 reviews)
(94 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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DeepLearning.AI
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Universidad Austral
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94 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 Oct 28, 2023
I need to use my on GCP to run the lab. Otherwise, very good introduction to get going on Transformers
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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