Stemming is a method of removing the suffix of the word and bringing it to a base word. Stemming is the normalization technique used in Natural language processing that reduces the number of computations required. We can do stemming in NLP using libraries such as PorterStemming, Snowball Stemmer, etc.
For example, we have the word ‘Eating, we remove the suffix ‘ing’ and bring that word to a base word ‘eat’.
Stemming is mainly used to reduce the dimensionality of data. In simple words, if there we have words like walk, walks, waited, waiting that are different but similar contextually. We bring these words base word ‘walk’ by removing suffixes from all the words.
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Also, watch this video on Sentiment Analysis:
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