Establishing Processes for Successful Data Management for AI Models to Improve AI-based Software Designs
Time: 11:30 am
day: Conference Day One
Details:
- Implement rigorous data validation and cleansing processes to ensure the reliability and accuracy of training datasets for AI models
- Establish robust, scalable infrastructure that supports seamless data collection, storage, and processing to handle large and diverse datasets efficiently
- Develop continuous monitoring and feedback loops to detect data drift, bias, and anomalies, ensuring ongoing model performance and alignment with software design goals
