Fundamental Concepts of Overfitting and Underfitting in Machine Learning

This module provides an intuitive introduction to the very fundamental concepts of overfitting and underfitting in machine learning. Machine learning models can never make perfect predictions: test error is never zero. This failure is due to a fundamental trade-off between modeling flexibility and the limited size of the training dataset.

This is a no brainer

This is a no brainer

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