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Mastering spaCy

Transformers and Transfer Learning

Explore the transformer architecture introduced in 2017 and how it revolutionizes NLP by using self-attention mechanisms. Understand the differences between transformers and LSTM, and discover how transfer learning with pre-trained models like BERT enhances NLP applications in spaCy.

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A milestone in NLP happened in 2017 with the release of the research paper Attention Is All You NeedVaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention Is All You Need. ArXiv./abs/1706.03762 by Vaswani et al., which introduced a brand-new machine learning idea and architecture—transformers. Transformers in NLP is a fresh idea that aims to solve sequential modeling tasks and targets some problems introduced by long short-term memory (LSTM) architecture ( ...