GitHub - manki11/Natural-Language-Processing: All the important steps for NLP using nltk

Natural Language Processing

Pre processing Data:

Tokenizing: Seperating of words or sentences.
Stop Words: Getting rid of useless words
Stemming: Converting all words into root.
Lemmatization: Better than stemming.
Spech Tagging: Making tuples of words with their tags(nouns, adverbs, adjectives)
Chunking: Grouping of similar grammar together
Chinking: Grouping of similar grammar together by selecting all and removing certain kind out.
Named Entity Recognition: Alternative to chunking/chinking.
Wordnet: To find synonyms/ antonyms/ meanings of words. Also used to find similarities between words.

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
.gitignore		.gitignore
chinking.py		chinking.py
chunking.py		chunking.py
lemmatizer.py		lemmatizer.py
named_entity_recognition.py		named_entity_recognition.py
readme.md		readme.md
speech_tagging.py		speech_tagging.py
stemming.py		stemming.py
stop_words.py		stop_words.py
tokenizing.py		tokenizing.py
wordnet.py		wordnet.py

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