Loss Function Explained For Noobs (How Models Know They Are Wrong)

Short summary

A beginner's guide explaining loss functions—how machine learning models measure prediction errors and improve over time through training.

• •Loss functions quantify how wrong a model's predictions are relative to actual values
• •Models use loss to adjust internal weights and reduce errors during training
• •Loss is the feedback mechanism that enables neural networks to learn iteratively

Generated with AI, which can make mistakes.