Answer / Radhey Shyam Sharma

Data normalization is a preprocessing technique applied to input data before feeding it into a machine learning model. The goal of normalization is to scale the values in the dataset to a common range, making them more suitable for certain algorithms and improving their convergence properties. Common normalization techniques include min-max scaling, z-score standardization, and power law normalization.

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