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Introduction.
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Explain the problem statement.
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Explain your notebook from start to finish.
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What is the learning rate?
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How does the learning rate affect overfitting and underfitting?
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Coding: Create a dummy Pipeline and add it to a ColumnTransformer.
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Coding: Use a different scaling method and a different imputation strategy.
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What is Data Preprocessing?
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What is EDA?
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What is Feature Engineering?
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What is Hyperparameter Tuning?
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What does random_state = 42 mean?
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Questions based on your notebook implementation.