Overfitting happens when a machine learning model becomes too complex, capturing noise in the training data rather than the true patterns. It’s crucial for anyone working on predictive models, as issues like overfitting and underfitting can ruin outcomes. Videos often cover concepts such as the K-Nearest Neighbor (KNN) algorithm, the relationship between bias and variance, and strategies for using models like Random Forests to improve accuracy.
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