Data Science and Machine Learning (Theory and Projects) A to Z - Overfitting, Underfitting, and Generalization: Generali

The video discusses regularization in machine learning, emphasizing its role in controlling model flexibility by constraining parameter values. It explores how to evaluate a model's generalization ability on unseen data, highlighting the importance of splitting data into training and validation sets. The video explains overfitting, where a model performs well on training data but poorly on unseen data, and suggests strategies to mitigate it, such as using more data or simpler models. It also addresses the challenge of balancing data allocation for training and validation to ensure accurate model evaluation.

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