Web Reference: Jul 23, 2025 · Explanation: 2D NumPy array a is normalized directly using global min-max scaling. Values are scaled to [0, 1] based on a.min () and a.max () and the result is converted to a list with .tolist () for readability. Normalization is an important step in preprocessing data for data analysis, machine learning, and deep learning. By normalizing your data, you’re converting it into a standardized format to ensure that it is more suitable for analysis and model training. In this tutorial, we’ll explore three main normalization techniques: 1. Min-Max Scaling, which ... normalize requires a 2D input. You can pass the axis= argument to specify whether you want to apply the normalization across the rows or columns of your input array. Note that the 'norm' argument of the normalize function can be either 'l1' or 'l2' and the default is 'l2'.
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