Implementing feedback systems – Mitigating Algorithmic Bias and Tackling Model and Data Drift
Implementing feedback systems Feedback isn’t just for Amazon reviews or post-workshop surveys. In the world of ML, feedback systems can act as our reality checks. They can help us understand whether our model’s predictions align with the evolving real world. Feedback can come from various sources, such as users flagging incorrect predictions or automated checks […]