Preprocessing Text Using Python and NLTK

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In this video, we explore how to preprocess text using the Natural Language Toolkit (NLTK) in Python. Preprocessing text is an essential step in natural language processing (NLP) and can help improve the accuracy of your models. We cover various techniques: tokenization, stop word removal, stemming, and lemmatization. We also walk through examples of how to implement these techniques using NLTK. By the end of this video, you'll have a solid understanding of how to preprocess text using NLTK and be able to apply these techniques to your own NLP projects.

00:00 Intro
00:23 Tokenization
01:30 Stop word removal
02:37 Stemming
03:37 Lemmatization
  1. CompLing
  2. NLTK
  3. Natural Language Processing
  4. Text Preprocessing
  5. Tokenization
  6. Stemming
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