Deep Learning - Crash Course 2023 - Train Test Split

The video tutorial explains the importance of splitting data into training and test sets in machine learning. It demonstrates how to use the scikit-learn library to perform a train-test split, initially in a 75-25 ratio, and then adjusts for deep learning with a 90-10 ratio. The tutorial highlights the significance of using the 'stratify' parameter to ensure balanced data distribution and the 'random state' parameter for reproducibility. The video concludes by emphasizing the need for consistent data splits to achieve reliable model accuracy.

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