The Natural Language Toolkit (NLTK) is a powerful Python package for natural language processing (NLP). Here are some of the things you can do with it:Tokenizing: This is the process of breaking down text into words, phrases, symbols, or other meaningful elements called tokens1.
Filtering Stop Words: Stop words are words that you want to ignore, so you filter them out when you’re processing your text1.
Stemming: This is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form1.
Tagging Parts of Speech (POS): This involves labeling the words in your text by their part of speech1.
Lemmatizing: This is the process of grouping together the inflected forms of a word so they can be analyzed as a single item1.
Chunking: This involves grouping individual pieces of information into bigger pieces1.
Chinking: This is the process of removing a sequence of tokens from a chunk1.
Named Entity Recognition (NER): This is the process of finding and classifying named entities in text1.
Frequency Distribution: This allows you to count the frequency of words within a text1.
Sentiment Analysis: This involves determining the attitude or emotion of the writer or speaker based on the text23.
These are just a few examples. NLTK is a very robust library with many more features and capabilities4. It’s a great tool for anyone interested in text analysis, computational linguistics, and machine learning