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This book provides an accessible introduction to natural language processing, a field that underpins various language technologies such as predictive text, email filtering, automatic summarization, and translation. It guides you in writing Python programs to handle large collections of unstructured text. You'll learn to access richly annotated datasets using diverse linguistic data structures and grasp the main algorithms for analyzing written communication's content and structure. With numerous examples and exercises, you'll acquire skills to extract information from unstructured text, analyze linguistic structure through parsing and semantic analysis, and access popular linguistic databases like WordNet and treebanks. The book integrates techniques from linguistics and artificial intelligence, equipping you with practical skills in natural language processing using Python and the Natural Language Toolkit (NLTK) open-source library. Whether you're interested in developing web applications, analyzing multilingual news, documenting endangered languages, or simply exploring a programmer's view of human language, this resource will be both fascinating and immensely useful.
Zakup książki
Natural language processing with Python, Steven Bird, Ewan Klein, Edward Loper
- Język
- Rok wydania
- 2009
- Oprawa
- (miękka)
Metody płatności
Brakuje nam tutaj Twojej recenzji.
- Tytuł
- Natural language processing with Python
- Język
- angielski
- Autorzy
- Steven Bird, Ewan Klein, Edward Loper
- Wydawca
- O'Reilly
- Rok wydania
- 2009
- Oprawa
- miękka
- Liczba stron
- 512
- ISBN10
- 0596516495
- ISBN13
- 9780596516499
- Seria
- Kategorie
- Tagi
- Poradniki, Technologia, Lingwistyka
- Ocena
- 4,1 z 5
- Opis
- This book provides an accessible introduction to natural language processing, a field that underpins various language technologies such as predictive text, email filtering, automatic summarization, and translation. It guides you in writing Python programs to handle large collections of unstructured text. You'll learn to access richly annotated datasets using diverse linguistic data structures and grasp the main algorithms for analyzing written communication's content and structure. With numerous examples and exercises, you'll acquire skills to extract information from unstructured text, analyze linguistic structure through parsing and semantic analysis, and access popular linguistic databases like WordNet and treebanks. The book integrates techniques from linguistics and artificial intelligence, equipping you with practical skills in natural language processing using Python and the Natural Language Toolkit (NLTK) open-source library. Whether you're interested in developing web applications, analyzing multilingual news, documenting endangered languages, or simply exploring a programmer's view of human language, this resource will be both fascinating and immensely useful.


