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Data Normalization and Min–Max Scaling are preprocessing techniques used to bring numerical features onto a common scale, which is essential for many machine learning algorithms. Data Normalization refers to the process of rescaling numerical data so that features contribute equally to model learning. Without normalization, features with ...
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