Deep learning and linguistic representation By Shalom Lappin.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9780367648749
- 410.285 LAP-D
Item type | Current library | Home library | Call number | Status | Date due | Barcode | |
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Dept. of Computational Biology and Bioinformatics Processing Center | Dept. of Computational Biology and Bioinformatics | 410.285 LAP-D (Browse shelf(Opens below)) | Available | DCB4122 |
Chapter 1 Introduction: Deep Learning in Natural Language Processing
Chapter 2 Learning Syntactic Structure with Deep Neural Networks
Chapter 3 Machine Learning and The Sentence Acceptability Task
Chapter 4 Predicting Human Acceptability Judgments in Context
Chapter 5 Cognitively Viable Computational Models of Linguistic Knowledge
Chapter 6 Conclusions and Future Work
Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks.
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