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Video

Automate Compliance and Governance in ML Production

As organizations grow and optimize business through AI, there is a pressing need to ensure robust governance of models used in business-critical applications and workflows. For both regulated and unregulated industries, it is crucial to incorporate data science best practices like model documentation, centralized monitoring of models, and tackling bias. Such a framework also enables organizations to meet government regulations and reduce overall risk from models in production.

In this session you will learn:

  • Key challenges involved in governing ML for regulated and unregulated industries
  • How to automatically uphold production models to the highest governance standards
  • Why Freddie Mac, a leading home mortgage company, is leveraging DataRobot for automated compliance and governance

Speaker

Brian Bell Jr.
Brian Bell Jr.

Senior Director, ML Production, DataRobot

  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
    Omair Tariq
    Omair Tariq

    Data Analyst, Symphony Post Acute Network

  • I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
    Oliver Rees
    Oliver Rees

    General Manager – Torque Data at Virgin Australia

  • At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
    Akshay Tandon
    Akshay Tandon

    VP of Strategy Analytics, LendingTree

  • We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
    Evariant