Quick Introduction to Bag-of-Words (BoW) and TF-IDF for Creating Features from Text
The Challenge of Making Machines Understand Text
“Language is a wonderful medium of communication”
You and I would have understood that sentence in a fraction of a second. But machines simply cannot process text data in raw form. They need us to break down the text into a numerical format that’s easily readable by the machine (the idea behind Natural Language Processing!).
This is where the concepts of Bag-of-Words (BoW) and TF-IDF come into play. Both BoW and TF-IDF are techniques that help us convert text sentences into numeric vectors.
I’ll be discussing both Bag-of-Words and TF-IDF in this article. We’ll use an intuitive and general example to understand each concept in detail.
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Let’s Take an Example to Understand Bag-of-Words (BoW) and TF-IDF
I’ll take a