Explain Data Normalisation. What is the need for it?

1.	Explain Data Normalisation. What is the need for it?
Answer» Data Normalisation is a technique in which data is transformed in such a WAY that they are EITHER dimensionless or have a SIMILAR distribution. It is also known as standardization and feature SCALING. It's a pre-processing procedure for the input data that removes redundant data from the dataset. Normalization provides each variable equal weights/importance, ensuring that no single variable biases model performance in its favour SIMPLY because it is larger. It vastly improves model precision by converting the values of numeric columns in a dataset to a similar scale without distorting the range of values.

Answer»

Data Normalisation is a technique in which data is transformed in such a WAY that they are EITHER dimensionless or have a SIMILAR distribution. It is also known as standardization and feature SCALING. It's a pre-processing procedure for the input data that removes redundant data from the dataset.

Normalization provides each variable equal weights/importance, ensuring that no single variable biases model performance in its favour SIMPLY because it is larger. It vastly improves model precision by converting the values of numeric columns in a dataset to a similar scale without distorting the range of values.

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