Interface administrators, Administrators (Semantic MediaWiki), Curators (Semantic MediaWiki), Editors (Semantic MediaWiki), Suppressors, Administrators
7,785
edits
Attention: Difference between revisions
Created page with "{{see also|Machine learning terms}} ==Introduction== Attention is a technique in machine learning that allows a model to focus on specific parts of an input while making predictions. Attention mechanisms enable models to selectively focus on certain parts of an input sequence - making them useful in tasks involving sequential or structured data. Attention models have become increasingly popular over the last few years, particularly in natural language processing (NLP). A..."
(Created page with "{{see also|Machine learning terms}} ==Introduction== Attention is a technique in machine learning that allows a model to focus on specific parts of an input while making predictions. Attention mechanisms enable models to selectively focus on certain parts of an input sequence - making them useful in tasks involving sequential or structured data. Attention models have become increasingly popular over the last few years, particularly in natural language processing (NLP). A...") |
(No difference)
|