Overfitting

Definition

When a model learns the training data too well, including noise, and fails to generalize to new data.

Detailed Explanation

Understanding Overfitting is crucial for mastering modern AI. It describes when a model learns the training data too well, including noise, and fails to generalize to new data.

The significance of Overfitting cannot be overstated. As AI systems become more complex, mechanisms like this ensure scalability and accuracy.

Applications of Overfitting

Real-world applications include advanced natural language processing, computer vision systems, and automated decision-making frameworks.

Last updated: February 2026