What are the challenges of feedback loops in machine learning?

What are the challenges of feedback loops in machine learning?

Feedback loops in machine learning can lead to issues like model bias, overfitting, and data drift.

Can you explain how model bias occurs in feedback loops?

Model bias occurs when the model learns from skewed data, reinforcing existing biases in predictions.

What are some strategies to mitigate these challenges?

Strategies include regular model evaluation, diverse training data, and implementing feedback monitoring systems.

How does data drift affect machine learning models?

Data drift can cause models to become less accurate over time as the underlying data distribution changes.