Difference between revisions of "Natural Language Toolkit (NLTK)"
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* [http://www.kdnuggets.com/2018/10/machines-understand-language-introduction-natural-language-processing.html How Machines Understand Our Language: An Introduction to Natural Language Processing | Emma Grimaldi - KDnuggets] | * [http://www.kdnuggets.com/2018/10/machines-understand-language-introduction-natural-language-processing.html How Machines Understand Our Language: An Introduction to Natural Language Processing | Emma Grimaldi - KDnuggets] | ||
− | NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. | + | NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Lexical Corpus Integration(WordNet, Stopwords, etc), Tokenization, Sentiment Analysis |
http://cdn-images-1.medium.com/max/800/1*jfZ4uK1Tko0TFugEk9oXDw.png | http://cdn-images-1.medium.com/max/800/1*jfZ4uK1Tko0TFugEk9oXDw.png |
Revision as of 01:35, 6 April 2019
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- Natural Language Tools & Services
- Natural Language Toolkit | NLTK.org
- NLP Tutorial Using Python NLTK (Simple Examples)
- How to do Natural Language Processing | Anaconda Documentation
- How Machines Understand Our Language: An Introduction to Natural Language Processing | Emma Grimaldi - KDnuggets
NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Lexical Corpus Integration(WordNet, Stopwords, etc), Tokenization, Sentiment Analysis