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Question & Answer
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By allowing models to leverage previously learned representations from related tasks
By requiring extensive labeled data for every single task
By focusing solely on the syntax of the language being processed
By utilizing random initializations for model weights
Understanding the Answer
Let's break down why this is correct
Transfer learning lets a model use knowledge it learned from other tasks. Other options are incorrect because Some think transfer learning needs lots of labeled data for each task; People sometimes think transfer learning focuses only on syntax.
Key Concepts
Sequence Transduction Models
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Deep Dive: Sequence Transduction Models
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Definition
Sequence transduction models are based on complex neural networks that encode and decode sequences. These models aim to translate input sequences into output sequences and have seen advancements in performance and efficiency.
Topic Definition
Sequence transduction models are based on complex neural networks that encode and decode sequences. These models aim to translate input sequences into output sequences and have seen advancements in performance and efficiency.
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