Machine learning and deep learning in natural language processing:
"Natural Language Processing (NLP) is a subset of AI, linguistics and computer science, and is concerned with generation, recognition and understanding of human language, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of word...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton
CRC Press
2024
|
| Ausgabe: | First edition |
| Schlagworte: | |
| Online-Zugang: | DE-824 Volltext |
| Zusammenfassung: | "Natural Language Processing (NLP) is a subset of AI, linguistics and computer science, and is concerned with generation, recognition and understanding of human language, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the Natural Language Processing field, in particular, about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content - like emotions but also satirical expressions - and applications in the healthcare field. NLP has the potential to be a disruptive technology in the fields of healthcare, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson's disease, or help psychotherapists. The book is intended for a wide audience: beginners will find chapters providing a general introduction to the NLP techniques useful, while experienced professionals would appreciate the chapters about advanced management of emotion, empathy, and non-literal content"-- |
| Beschreibung: | OCLC-licensed vendor bibliographic record |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9781003296126 1003296122 9781000960853 1000960854 9781000960891 1000960897 |
| DOI: | 10.1201/9781003296126 |
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| 100 | 1 | |a Pillai, Anitha S. |d 1967- |e Verfasser |4 aut | |
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Datensatz im Suchindex
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| author | Pillai, Anitha S. 1967- Tedesco, Roberto |
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| dewey-full | 006.3/5 |
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| dewey-ones | 006 - Special computer methods |
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| discipline | Informatik |
| doi_str_mv | 10.1201/9781003296126 |
| edition | First edition |
| format | Electronic eBook |
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| id | DE-604.BV050218272 |
| illustrated | Not Illustrated |
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| isbn | 9781003296126 1003296122 9781000960853 1000960854 9781000960891 1000960897 |
| language | English |
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| publishDate | 2024 |
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| publisher | CRC Press |
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| spelling | Pillai, Anitha S. 1967- Verfasser aut Machine learning and deep learning in natural language processing edited by Anitha S. Pillai, Roberto Tedesco First edition Boca Raton CRC Press 2024 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier OCLC-licensed vendor bibliographic record "Natural Language Processing (NLP) is a subset of AI, linguistics and computer science, and is concerned with generation, recognition and understanding of human language, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the Natural Language Processing field, in particular, about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content - like emotions but also satirical expressions - and applications in the healthcare field. NLP has the potential to be a disruptive technology in the fields of healthcare, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson's disease, or help psychotherapists. The book is intended for a wide audience: beginners will find chapters providing a general introduction to the NLP techniques useful, while experienced professionals would appreciate the chapters about advanced management of emotion, empathy, and non-literal content"-- COMPUTERS / Natural Language Processing bisacsh COMPUTERS / Neural Networks bisacsh Natural language processing (Computer science) Machine learning Deep learning (Machine learning) Tedesco, Roberto aut Erscheint auch als Druck-Ausgabe 9781032264639 Erscheint auch als Druck-Ausgabe 9781032282879 https://doi.org/10.1201/9781003296126 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Pillai, Anitha S. 1967- Tedesco, Roberto Machine learning and deep learning in natural language processing COMPUTERS / Natural Language Processing bisacsh COMPUTERS / Neural Networks bisacsh Natural language processing (Computer science) Machine learning Deep learning (Machine learning) |
| title | Machine learning and deep learning in natural language processing |
| title_auth | Machine learning and deep learning in natural language processing |
| title_exact_search | Machine learning and deep learning in natural language processing |
| title_full | Machine learning and deep learning in natural language processing edited by Anitha S. Pillai, Roberto Tedesco |
| title_fullStr | Machine learning and deep learning in natural language processing edited by Anitha S. Pillai, Roberto Tedesco |
| title_full_unstemmed | Machine learning and deep learning in natural language processing edited by Anitha S. Pillai, Roberto Tedesco |
| title_short | Machine learning and deep learning in natural language processing |
| title_sort | machine learning and deep learning in natural language processing |
| topic | COMPUTERS / Natural Language Processing bisacsh COMPUTERS / Neural Networks bisacsh Natural language processing (Computer science) Machine learning Deep learning (Machine learning) |
| topic_facet | COMPUTERS / Natural Language Processing COMPUTERS / Neural Networks Natural language processing (Computer science) Machine learning Deep learning (Machine learning) |
| url | https://doi.org/10.1201/9781003296126 |
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