What are feedback loops in machine learning?
Feedback loops occur when the output of a model influences future inputs, potentially leading to biased results.
How can I identify feedback loops in my ML model?
You can identify feedback loops by monitoring model performance over time and analyzing input-output relationships.
What strategies can I use to manage these feedback loops?
Strategies include regular model retraining, using diverse data sources, and implementing feedback mechanisms to correct biases.
Can you give an example of a feedback loop in a real-world application?
Sure! In recommendation systems, user interactions can create feedback loops that reinforce certain preferences, skewing results.
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