Domain 5. Managing AI

Task 1: Evaluating Model Performance and Accuracy

  • Implement quality assurance processes for AI models
  • Apply model validation techniques using appropriate validation data
  • Implement strategies to address overfitting and underfitting
  • Align model performance with business key performance indicators
  • Assess models against technical KPIs and requirements
  • Implement iterative improvement based on evaluation findings

Task 2: Deploying Models for Production Environments

  • Transition AI models from training to inference phases
  • Implement operationalization strategies for production deployment
  • Configure on-premise deployments for sensitive or high-performance needs
  • Leverage cloud platforms for scalable AI deployment
  • Select appropriate cloud-based machine learning services
  • Manage data lifecycles throughout the production environment
  • Create procedures for model updates and version control

Leave a Reply