Data Scaling

Data scaling is a crucial step in preparing data for machine learning and AI. Its purpose is to normalize and standardize the data to a consistent level. This ensures that no particular feature dominates the data and causes any biased predictions. Additionally, data scaling improves the performance of optimization algorithms that are used in training deep neural networks. Normalization and standardization are two frequently used data scaling methods in AI and Machine Learning.

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