sgrvinod/a-PyTorch-Tutorial-to-Sequence-Labeling
Empower Sequence Labeling with Task-Aware Neural Language Model | a PyTorch Tutorial to Sequence Labeling
This tutorial helps machine learning practitioners build models that can automatically tag each word in a sentence with relevant labels like entities or parts of speech. It takes raw text as input and produces text with each word categorized. This is ideal for natural language processing engineers, data scientists, or researchers working on text analysis tasks.
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Use this if you need to precisely label specific words or phrases within text based on their context, like identifying names, locations, or parts of speech, and you are comfortable with deep learning frameworks.
Not ideal if you're looking for a simple, out-of-the-box solution without diving into model implementation, or if your primary task is general text classification rather than detailed word-level tagging.
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Jun 03, 2020
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