Document Clustering using K Means

Clustering documents is an important task as it groups similar documents together which can be used for a variety of tasks such as recommendations, similarity detection, creating dataset of a topic, generate new data following same pattern and so on. Clustering has always been a central task in Natural Language Processing and in this article, we use ideas from TF IDF and similarity metrics to use K Means clustering algorithm to cluster documents.

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