What role does positional encoding play in transformer models, and why is it necessary for understanding the order of words in a sentence?
Tuesday, 11 June 2024 by EITCA Academy
Transformer models have revolutionized the field of natural language processing (NLP) by enabling more efficient and effective processing of sequential data such as text. One of the key innovations in transformer models is the concept of positional encoding. This mechanism addresses the inherent challenge of capturing the order of words in a sentence, which is
- Published in Artificial Intelligence, EITC/AI/ADL Advanced Deep Learning, Natural language processing, Advanced deep learning for natural language processing, Examination review
Tagged under: Artificial Intelligence, NLP, Positional Encoding, Self-Attention, Sequence Modeling, Transformers