Day 3: Tokenization and stopword removal

Tokenization and stop word removal are two important steps in pre-processing text data for natural language processing (NLP) tasks. These steps help to prepare the text data for further analysis, modelling, and modelling training. Tokenization is the process of breaking down a larger piece of text into smaller units, called tokens, which can then be…

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What is Stop word in NLP?

Stop words are the most common words in any language that do not carry any meaning and are usually ignored by NLP. In English, examples of stop words are “a”, “and”, “the” and “of”. In NLP, stop words are typically removed from a text before it is processed for analysis. This is done to reduce…

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