Build Machine Learning Models, Data collection and processing, Feature engineering, Model build, Model validation and testing, Machine learning model monitoring, Ensure continuous operation and availability, Feedback loops and
continuous model retraining, Capitalization, replication, and acceleration, Metrics and ROI, Machine learning model control, Versioning to enable functionality to go back in time, Audit, balance,
and control, Templates and reusable components, Machine learning model integration, User acceptance test and preproduction, Automated Deployment Integration with downstream Applications, Adoption of end users and business impact
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