What is the impact of loss function in machine learning?

What is the impact of loss function in machine learning?

The loss function measures how well a machine learning model's predictions match the actual outcomes. It guides the optimization process.

Can you explain how different loss functions affect model performance?

Different loss functions can lead to varying model behaviors. For instance, mean squared error is sensitive to outliers, while absolute error is more robust.

What are some common loss functions used in deep learning?

Common loss functions in deep learning include cross-entropy loss for classification tasks and mean squared error for regression tasks.

How do I choose the right loss function for my model?

Choosing the right loss function depends on your specific task, the nature of your data, and the desired outcome. It's often a matter of experimentation.