Machine Learning Fundamentals: Regularization and Cross-validation

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Introduces supervised learning, covering classification, regression, model optimization, overfitting, and kernel methods.

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Explores overfitting, regularization, and cross-validation in machine learning, emphasizing the importance of model complexity and different cross-validation methods.

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