What do you mean by Normalisation? Difference between Normalisation and Standardization?

Data Science, AI and ML
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Normalisation is a process of bringing the features in a simple range, so that model can perform well and do not get inclined towards any particular feature.

For example – If we have a dataset with multiple features and one feature is the Age data which is in the range 18-60 , Another feature is the salary feature ranging from 20000 – 2000000. In such a case, the values have a very much difference in them. Age ranges in two digits integer while salary is in range significantly higher than the age. So to bring the features in comparable range we need Normalisation.

Both Normalisation and Standardization are methods of Features Conversion. However, the methods are different in terms of the conversions. The data after Normalisation scales in the range of 0-1. While in case of Standardization the data is scaled such that it means comes out to be 0.