In an e-commerce recommendation system powered by ML, users are consistently being recommended irrelevant items. How would you troubleshoot and resolve this issue?
- Optimize server performance.
- Gather more user data.
- Implement a better recommendation algorithm.
- Analyze and improve data quality and feature engineering.
To troubleshoot and resolve the issue of irrelevant recommendations, it's essential to analyze and improve the quality of the data used in the recommendation system and fine-tune feature engineering. This will lead to better model performance and more relevant recommendations.
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