Difference between revisions of "Natural Language Toolkit (NLTK)"
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* [http://likegeeks.com/nlp-tutorial-using-python-nltk/ NLP Tutorial Using Python NLTK (Simple Examples)] | * [http://likegeeks.com/nlp-tutorial-using-python-nltk/ NLP Tutorial Using Python NLTK (Simple Examples)] | ||
* [http://docs.anaconda.com/anaconda-cluster/howto/spark-nltk/ How to do Natural Language Processing | Anaconda Documentation] | * [http://docs.anaconda.com/anaconda-cluster/howto/spark-nltk/ How to do Natural Language Processing | Anaconda Documentation] | ||
| + | * [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. | ||
Revision as of 13:50, 3 November 2018
- Natural Language Tools
- 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.
