Introduction to Azure AI Evaluation¶
Learn about comprehensive evaluation of AI models and agents using Azure AI Evaluation, ensuring optimal performance and reliability.
Understanding AI Evaluation¶
1. Evaluation Purpose¶
- Performance measurement
- Quality assessment
- Reliability verification
- Security validation
- Cost optimization
- Improvement identification
2. Evaluation Scope¶
- Model capabilities
- Agent behaviors
- System performance
- Integration efficiency
- Resource utilization
- User experience
3. Evaluation Benefits¶
- Quality assurance
- Performance optimization
- Cost management
- Risk mitigation
- Continuous improvement
- Compliance verification
Types of Evaluation¶
1. Model Evaluation¶
- Accuracy assessment
- Performance metrics
- Resource efficiency
- Response quality
- Error analysis
- Cost effectiveness
2. Agent Evaluation¶
- Behavior analysis
- Task completion
- Decision quality
- Response appropriateness
- Error handling
- Resource usage
3. System Evaluation¶
- Integration testing
- Performance analysis
- Security assessment
- Scalability testing
- Reliability checks
- Cost efficiency
Evaluation Metrics¶
1. Performance Metrics¶
- Response accuracy
- Processing time
- Resource usage
- Error rates
- Throughput
- Latency
2. Quality Metrics¶
- Output relevance
- Response coherence
- Task completion
- User satisfaction
- Error handling
- Recovery efficiency
3. Operational Metrics¶
- Resource utilization
- Cost efficiency
- Availability
- Reliability
- Security compliance
- Maintenance needs
Evaluation Framework¶
1. Evaluation Planning¶
- Objective definition
- Metric selection
- Resource allocation
- Timeline planning
- Team coordination
- Documentation requirements
2. Evaluation Process¶
- Data preparation
- Test execution
- Result collection
- Analysis methods
- Report generation
- Improvement planning
3. Continuous Improvement¶
- Result analysis
- Performance optimization
- Resource adjustment
- Process refinement
- Documentation updates
- Knowledge sharing
Interactive Workshop¶
To get hands-on experience with Azure AI Evaluation, we've prepared an interactive Jupyter notebook that will guide you through: - Setting up evaluation metrics - Running evaluations on your customer service agent - Analyzing and interpreting results - Implementing best practices for evaluation
Launch Interactive Evaluation Workshop
This notebook provides a practical implementation of the concepts covered in this introduction. You'll work directly with the Azure AI Evaluation SDK to assess and improve your customer service agent's performance.
Next: Setting Up Evaluation