Two minutes NLP -- Learn TF-IDF with easy examples

TF-IDF (Term Frequency-Inverse Document Frequency) is a way of measuring how relevant a word is to a document in a collection of documents. TF-IDF has many uses, such as in information retrieval, text analysis, keyword extraction, and as a way of obtaining numeric features from text for machine learning algorithms. TF-IDF was first designed for document search and information retrieval, where a query is run and the system has to find the most relevant documents. Suppose the query is the text "The bug". The system would give each document a higher score proportionally to the frequencies of the query words found in the document, weighting more rare words like "bug" with respect to common words like "the".