Evaluating the impact that machine learning operations (MLOps) will have on the business is an essential part of any AI/ML business case. The business is looking to use AI/ML as a competitive advantage, but often stops short at looking only at the Data Science Investment. As an MLOps professional there are critical outcomes you can measure and KPIs to track that will help you justify the investment in platforms and applications to support ML at scale.
Use these measures and KPIs to justify investment in an ML-focused lifecycle required to build, deploy and operate enterprise-ready models that generate real value.
This webinar will discuss:
- 5 areas where MLOps has a measurable impact
- 5 best practices KPIs to monitor to demonstrate value
- Real-world examples of how organizations have made this pay off for their business