Standardization and Normalization are not mandatory approaches and can be avoided in some cases, but some models like neural networks, SVM, etc. require the data to either be standardized or normalized. You can try running the model with and without standardization or normalization and evaluate the performance. If performance improves with standardization or normalization then keep it, if performance declines then remove it
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