Evals: What Software Engineers Should Learn From Data Scientists

1. 1Adopt evaluation metrics to measure AI model performance
2. 2Implement iterative development to refine models based on feedback
3. 3Collaborate with data scientists to integrate evaluation metrics into the development workflow
4. 4Use data science techniques to monitor and improve model performance in production
5. 5Apply agile development principles to facilitate rapid iteration and improvement

Software engineers and data scientists can collaborate to improve the production readiness of AI models by adopting evaluation metrics and iterative development, leading to more successful deployments

💡 Incorporating evaluation metrics and iterative development into the software engineering workflow can significantly improve AI model production readiness

🚀 Improve AI model deployment by learning from data scientists! Adopt eval metrics, iterate, and collaborate to achieve production readiness 🚀