What are feedback loops in machine learning?
An example of an AI chatbot conversation about feedback loops in machine learning.
What are feedback loops in machine learning?
Feedback loops in machine learning refer to the process where the output of a model is used as input for future predictions, allowing the model to learn and adapt over time.
Can you give me an example of a feedback loop?
Sure! A common example is in recommendation systems, where user interactions with recommended items influence future recommendations.
How do feedback loops improve model accuracy?
Feedback loops help improve model accuracy by continuously updating the model with new data, allowing it to learn from its mistakes and adapt to changing patterns.
Are there any risks associated with feedback loops?
Yes, risks include overfitting to noise in the data or creating biased models if the feedback is not representative of the broader population.
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