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nice
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good sir g
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good
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I learned about the difference between Feature Scaling and Normalization.
Scaling: Scale the data into a range without changing its distribution.
Normalization: Scaling the data points individually and also changing the distribution.
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Done
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Done
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I learned in this video Scaling and Normalization.
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I learned in this lecture about Scaling and Normalization.
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Feature scaling (standardization) transforms features to have a zero mean and unit variance. It is useful when the scale of the features needs to be consistent across all variables.Normalization scales features to a specific range, typically between 0 and 1. It is useful when the range of feature values needs to be controlled or when specific algorithms require input in a certain range.
The function of STANDARDIZATION is to bring the data to scale, and the function of NORMALIZATION is to have an impact on the distribution of the data.
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Scaling:- To change the range of data without changing the shape of the data.
Normalization:- Transform data into scale and change its distribution.
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