Deep Learning - Crash Course 2023 - Data Standardization - 2

The video tutorial explains the process of standardizing data using the StandardScaler to achieve zero mean and unit variance. It emphasizes the importance of splitting the dataset into training and testing sets before applying the scaler to prevent information leakage. The tutorial also covers the correct method of applying the scaler: fitting and transforming the training data, then using the same scaling parameters to transform the test data. A code demonstration is provided to illustrate these concepts.

What is the significance of preventing information leakage from the test data set into the training data set?

Describe the process of transforming the test data set using the scaling values from the training data set.

What are the final mean and standard deviation values of the test data set after transformation?