What is a custom loss function in machine learning?

What is a custom loss function in machine learning?

A custom loss function is a user-defined function that measures how well a machine learning model performs, tailored to specific needs.

Can you give me an example of when to use a custom loss function?

Sure! If you're working on a medical diagnosis model, you might want to penalize false negatives more than false positives, so a custom loss function can help.

How do I implement a custom loss function in TensorFlow?

In TensorFlow, you can define a custom loss function as a Python function and then pass it to the model's compile method using the 'loss' parameter.

Are there any common pitfalls when creating custom loss functions?

Yes, common pitfalls include not properly normalizing the outputs or gradients, which can lead to unstable training.