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Monitoring Models at Scale


Catch this Domino webinar on monitoring models at scale, Dec 11 @ 10am PT, covering detecting changes in pattern of real-world data your models are seeing in production, tracking how model accuracy and other quality metrics are changing over time, and getting alerted when health checks fail so that resolution workflows can be triggered.



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Domino Monitoring Models
 

As more models go to production, managing and monitoring them becomes more onerous. Without proactive monitoring of production models, organizations are exposed to the risk of poor predictions on evolving data affecting their business outcomes.

Domino enables you to standardize model monitoring across all your data science teams. Key stakeholders get continuous visibility, and teams can initiate proactive actions before your business gets negatively impacted due to model decay. It frees your data scientists to work on building newer models, and facilitates your IT/Ops teams to take charge of monitoring in-production models.

Join this webinar to learn how Domino can help you monitor your models with:

  • Drift Checks: Detecting changes in pattern of real-world data your models are seeing in production.
  • Quality Checks: Tracking how model accuracy and other quality metrics are changing over time.
  • Health Alerts: Getting alerted when health checks fail so that resolution workflows can be triggered.

Can't attend the live webinar on December 11 at 10am PT? Register now, and you will receive a copy of the recording shortly after the live session!


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