Managing Models in Uncertain Times

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Presented by DataRobot

DataRobot is the leader in enterprise AI, delivering trusted AI technology and ROI enablement services to global enterprises. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models.

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Monitoring and managing your production models in normal times is tricky enough. With the levels of uncertainty introduced by COVID-19, this critical requirement is amplified even further. If left unchecked, this volatility will cause your models to decay, creating havoc with business-critical processes.

DataRobot believes this situation is preventable with effective machine learning operations best practices and we would like to share these with you.

Join us to learn more about ML Ops. We will discuss proven and scalable methodologies for production model deployment, monitoring, and lifecycle management. We will address key questions such as:

  • How do I maintain high-performing models in production?
  • How do I know when my production models start to become unreliable?
  • How do I quickly manage my models once their performance has decayed?
  • How do I move fast while also increasing scrutiny, compliance, and transparency around your ML Ops processes?
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