Data Preparation
Data Normalization
The process of scaling individual data points to a common scale, often to improve the performance of machine learning models.
Expanded definition
Data normalization is a crucial preprocessing step that transforms the features in a dataset to have a uniform scale, typically between 0 and 1 or with a mean of 0 and standard deviation of 1. This helps models converge faster during training and improves accuracy. Common normalization techniques include Min-Max scaling and Z-score normalization, each serving specific purposes depending on the dataset and the model being used.
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