![]() There are plenty of ways to perform vectorization, as we’ll see shortly, ranging from naive binary term occurrence features to advanced context-aware feature representations. Understanding Vectors From a Machine Learning Perspective The idea is to get some distinct features out of the text for the model to train on, by converting text to numerical vectors. In Machine Learning, vectorization is a step in feature extraction.This approach has been there ever since computers were first built, it has worked wonderfully across various domains, and it’s now used in NLP. ![]() text ) into vectors of real numbers which is the format that ML models support.
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