Lesson 9 of 13
Already have access? Sign in here
Already have access? Sign in here
Ask questions about this lesson and get instant answers.
A model's goal is to generalize: perform well on new data it has not seen during training. Two common failures prevent this. Overfitting occurs when a model learns the training data too well, including its noise and quirks, and fails to generalize. Underfitting occurs when a model is too simple to capture the true patterns in the data. Understanding these failure modes is central to building effective machine learning models.
A model's goal is to generalize: perform well on new data it has not seen during training. Two common failures prevent this. Overfitting occurs when a model learns the training data too well, including its noise and quirks, and fails to generalize. Underfitting occurs when a model is too simple to capture the true patterns in the data. Understanding these failure modes is central to building effective machine learning models.