Discuss the importance of data : Test-Train split in Python

The video tutorial explains the concept of test train split, a method used to divide data into training and testing sets, typically in an 80-20 ratio. It highlights the importance of using the sklearn library for this process and introduces the random set parameter to ensure consistent data splits for model evaluation. The tutorial also covers the outputs of the train test split function, including X train, X test, Y train, and Y test, and their roles in model training and evaluation.

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