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Semi-Supervised Learning in NLP by 22139012 is a document available to read on EtoBox.
What is Semi-Supervised Learning in NLP about?
The document discusses semi-supervised learning techniques for Natural Language Processing (NLP), focusing on pre-training, self-training, and consistency regularization. It highlights the importance of leveraging unlabeled data in NLP due to the limited availability of labeled datasets across various languages. Additionally, it outlines the success of deep learning in NLP and related fields, emphasizing the role of better algorithms, hardware, and larger datasets in driving advancements.
- Author
- 22139012
- Language
- EN