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README.md
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### Recommendations
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- **Continuous Monitoring:** Regularly monitor the model's performance on new data to ensure its effectiveness and reliability over time.
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- **Error Analysis:** Conduct thorough error analysis to identify common patterns of misclassifications and areas for improvement.
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- **Fine-Tuning:** Consider fine-tuning the model further based on feedback and insights from users,
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- **Model Interpretability:** Explore techniques for explaining the model's predictions, such as attention mechanisms or feature importance analysis, to increase trust and understanding of its decisions.
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### Recommendations
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- **Continuous Monitoring:** Regularly monitor the model's performance on new data to ensure its effectiveness and reliability over time.
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- **Error Analysis:** Conduct thorough error analysis to identify common patterns of misclassifications and areas for improvement.
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- **Fine-Tuning:** Consider fine-tuning the model further based on feedback and insights from users, to enhance its domain-specific performance.
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- **Model Interpretability:** Explore techniques for explaining the model's predictions, such as attention mechanisms or feature importance analysis, to increase trust and understanding of its decisions.
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