This pack provides a comprehensive set of prompts for managing the entire lifecycle of machine learning models, from deployment and monitoring to retraining and ethical considerations.
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Generate a comprehensive incident response plan for production machine learning models, covering detection, analysis, and resolution.
Generate a comprehensive design for an ML model monitoring dashboard, specifying key metrics and visualization types.
Create a detailed outline for an automated machine learning model deployment pipeline, from staging to production.
Formulate a strategic plan for retraining machine learning models, including triggers, data pipelines, and validation steps.
Analyze and identify potential biases and fairness issues within a machine learning model, suggesting mitigation strategies.
