#Standardization|#StandardScaler|#Python|#ML|Data Preprocessing in Machine Learning|Standardization

Gaussian distribution is a normal distribution which is of bell curved data.
1. Standardization is used to tranform the data attributes with a Gaussian distribution.
2. Algorithms like linear and logistic regression

Ans 1: Standardization is used to transform the data attributes with a gaussian distribution. Ans 2: Standardization is useful in algos like linear regression, logistic regression.

Ans 1: Standardization is used to transform the data attributes with a gaussian distribution. Ans 2: Standardization is useful in algos like linear regression, logistic regression, etc

1.Answer -- Standardisation is used to transform data attributes with a gaussian distribution that produces better result with rescaled data.
2.Answer -- Linear regression algorithm, Logistics regression algorithm

1. Standardization transforms data attributes with a Gaussian distribution that produces better results with rescaled data
2. Algorithms like Linear Regression, Logistics Regression.

1. Standardization transforms data attributes with a Gaussian distribution that produces better results with rescaled data.
2. Standardisation is useful in Algorithms like Linear Regression, Logistic Regression.

1. Standardisation transforms data attributes with a gaussian distribution that produces results with rescaled data. 2. Algorithms like Linear Regression, Logistic Regression.

1. Standardization transforms data attributes with a Gaussian distribution that produces better results with rescaled data.
2. Algorithms like Linear Regression, Logistic Regression

1.Standardization transforms data attributes with a Gaussian distribution that produces better results with rescaled data.
2.Algorithms like Linear regression, Logistic regression

1. Standardization transforms data attributes with a Gaussian distribution that produces better results with rescaled data
2. Algorithms like Linear Regression, Logistic Regression etc..

1. Standardization transforms data attributes with a Gaussian distribution that produces better results with rescaled data.
2. Algorithms like Linear Regression, Logistic Regression.

1. Standardization is used to transform data attributes with a Gaussian distribution that produces better results with rescaled data
2. Standardization is used in Algorithms like Logistic Regression, Linear Regression etc.

1. Standardization transforms data attributes with a Gaussian distribution that produces better results with rescaled data
2. Algorithms like Linear Regression, Logistic Regression

1.Standardization is used to transforms the data attributes with a gaussian distribution.
2. Standardization is useful in algos like Linear Regression,logistic regression etc.