Stemming vs Lemmatization in NLP: Must-Know Differences

This article was published as a part of the Data Science Blogathon. In the field of Natural Language Processing i.e., NLP, Lemmatization and Stemming are Text Normalization techniques. These techniques are used to prepare words, text, and documents for further processing. Languages such as English, Hindi consists of several words which are often derived from one another. Further, Inflected Language is a term used for a language that contains derived words. For instance, word "historical" is derived from the word "history" and hence is the derived word.