Build Enterprise Solutions For Model Operations & Governance
By Harish Doddi, CPO & Co-Founder
In this episode of the Data Exchange Ben Lorica speaks with Harish Doddi, co-founder of Datatron, a startup focused on helping companies operationalize machine learning. Over the past two years, Harish has worked closely with enterprises to understand their needs in the areas of model operations and model governance. Last year Harish and Ben, along with David Talby, wrote two articles on these topics. In the first article, we described these emerging areas (“What are model governance and model operations?”), and in the second we listed lessons that ML engineers can draw from two highly regulated industries (“Managing machine learning in the enterprise: Lessons from banking and health care”).
As machine learning becomes widely deployed, organizations will need to develop processes and tools to ensure that models behave as intended. This means having the right set of controls and validation steps in place.
Podcast Link
Topics Covered
  • MLOps, Model Governance, Model Observability.
  • How model governance is perceived and practiced in different industries.
  • Real-world examples of model governance, and organizational and staffing considerations that come into play.
  • CI/CD for machine learning.
  • Key enterprise features for model governance solutions.
Harish Doddi
CPO & Co-Founder
Over the past decade, Harish has focused on AI and data science. Before Datatron, he worked on the surge pricing model for Lyft, the backend for Snapchat Stories, the photo storage platform for Twitter, and designing and developing human workflow components for Oracle. Harish completed his master’s degree in computer science at Stanford, where he focused on systems and databases.
Hosted by Ben Lorica
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