Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Machine Learning Over

The video tutorial explains overfitting in machine learning, where a model becomes too flexible and memorizes training data instead of learning the underlying pattern. This results in poor performance on unseen data. The tutorial discusses the balance between overfitting and underfitting, emphasizing the importance of capturing the data's pattern rather than minimizing training loss. It also highlights methods to avoid overfitting, such as careful selection of hyperparameters.

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