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ai checklist
1. Project Planning
Define project goals and objectives
Identify stakeholders and their roles
Determine project timeline and milestones
Establish budget and resource allocation
2. Data Collection
Identify relevant data sources
Collect and preprocess data
Ensure data quality and integrity
Address data privacy and compliance issues
3. Model Development
Select appropriate AI algorithms and techniques
Split data into training, validation, and test sets
Train the model using selected algorithms
Evaluate model performance using metrics
4. Testing and Validation
Conduct thorough testing of the model
Validate results with a separate dataset
Perform bias and fairness assessments
Document testing procedures and outcomes
5. Deployment
Prepare the production environment
Integrate the AI model with existing systems
Monitor system performance and user feedback
Implement necessary security measures
6. Maintenance and Iteration
Regularly update the model with new data
Monitor performance and make adjustments as needed
Gather user feedback for continuous improvement
Document changes and maintain version control
7. Compliance and Ethics
Ensure compliance with relevant regulations
Address ethical considerations in AI use
Maintain transparency in AI decision-making
Educate stakeholders on AI implications and best practices
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