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Top 10 NLP Techniques in Data Science by Eshaan Pandey is a document available to read on EtoBox.

The document discusses the top 10 most used natural language processing (NLP) techniques for data science. It begins by explaining what NLP is and how it helps extract meaningful insights from unstructured text data. It then lists and describes the 10 most common NLP techniques: 1) tokenization, 2) stemming and lemmatization, 3) stop words removal, 4) term frequency-inverse document frequency (TF-IDF), 5) keyword extraction, 6) word embeddings, 7) sentiment analysis, 8) topic modeling, 9) text summarization

Author
Eshaan Pandey
Language
EN