Difference between revisions of "Natural Language Toolkit (NLTK)"
(Created page with "[http://www.youtube.com/results?search_query=NLTK+nlp+toolkit Youtube search...] * [http://likegeeks.com/nlp-tutorial-using-python-nltk/ NLP Tutorial Using Python NLTK (Simpl...") |
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| + | {{#seo: | ||
| + | |title=PRIMO.ai | ||
| + | |titlemode=append | ||
| + | |keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS | ||
| + | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
| + | }} | ||
[http://www.youtube.com/results?search_query=NLTK+nlp+toolkit Youtube search...] | [http://www.youtube.com/results?search_query=NLTK+nlp+toolkit Youtube search...] | ||
| + | [http://www.google.com/search?q=NLTK+nlp+toolkit+deep+machine+learning+ML+artificial+intelligence ...Google search] | ||
| + | * [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]] ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ... [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]] | ||
| + | * [http://www.nltk.org/ Natural Language Toolkit | NLTK.org] | ||
* [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://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.cs.bgu.ac.il/~elhadad/nlp18/NLTKPOSTagging.html Parts of Speech Tagging with NLTK | Michael Elhadad] [http://www.cs.bgu.ac.il/~elhadad/nlp18/NLTKPOSTagging.ipynb Jupyter Notebook] | ||
| + | * [http://textblob.readthedocs.io/en/dev/ TextBlob] ([[Python]]) is kind of an extension of NLTK. You can access many of NLTK's functions in a simplified manner; includes functionality from the Pattern library | ||
| − | <youtube> | + | 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 [http://wordnet.princeton.edu/ 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 ([http://wordnet.princeton.edu/ WordNet], Stopwords, etc), Tokenization, [[Sentiment Analysis]] |
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| + | <youtube>FLZvOKSCkxY</youtube> | ||
| + | <youtube>AKcxEfz-EoI</youtube> | ||
| + | <youtube>xc48ScRG5M8</youtube> | ||
| + | <youtube>R28h0CwJF6Q</youtube> | ||
Latest revision as of 20:02, 9 July 2023
Youtube search... ...Google search
- Large Language Model (LLM) ... Natural Language Processing (NLP) ...Generation ... Classification ... Understanding ... Translation ... 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
- Parts of Speech Tagging with NLTK | Michael Elhadad Jupyter Notebook
- TextBlob (Python) is kind of an extension of NLTK. You can access many of NLTK's functions in a simplified manner; includes functionality from the Pattern library
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
