Interpretable vector language models
Natural Language Processing (NLP) is a branch of computer science that focuses on the development of algorithms for understanding, interpreting, and generating human language texts. A crucial technique in NLP is word embedding, where models such as Word2Vec and GloVe assign vectors to words in a voc...
Saved in:
主要作者: | Eng, Jing Keat |
---|---|
其他作者: | Fedor Duzhin |
格式: | Final Year Project |
語言: | English |
出版: |
Nanyang Technological University
2023
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/166482 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Interpretable vector language models
由: Siow, Zi Hao
出版: (2024) -
Visualization of arrangements of carbon atoms in graphene layers by Raman mapping and atomic-resolution TEM
由: Cong, Chunxiao, et al.
出版: (2013) -
On storage codes allowing partially collaborative repairs
由: Liu, Shiqiu, et al.
出版: (2014) -
Classical self-orthogonal codes and their applications to quantum codes
由: Jin, Lingfei
出版: (2013) -
On constacyclic codes and their generalizations
由: Tharnnukhroh, Jareena
出版: (2022)