Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications Iterative Process: A step-by-step approach to building ML systems, allowing for flexibility and continuous improvement. Production-Ready Applications: Focus on creating systems that are reliable, scalable, and meet real-world requirements. Key Concepts: Data collection and preparation Model selection and training Evaluation and deployment Monitoring and maintenance Benefits: Improved accuracy and performance Reduced development time and costs * Increased confidence in ML systems