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Corralling machine learning for LCR inventory development

Watch this episode and earn a PDH:

This webinar covers:

Leveraging machine learning in inventory development and maintenance
Reviewing outputs for accuracy
Reviewing how these models tie into project planning and field work
Proposed guidelines for responsibly using machine learning that regulators can consider

In October 2024, the EPA finalized the Lead and Copper Rule Improvements (LCRI), with most requirements starting in late 2027. This guidance remains relevant for using machine learning and predictive modeling to build service line inventories with LCRI deadlines in mind. For the latest information on the rule, read "Challenges to the LCRI: What do they mean for you?"

Don't have time to watch the full webinar below? Check out our recap article, "Corralling Machine Learning for Service Line Inventory Development."

Corralling machine learning for inventory development

Meet the panelists

Joanna Cummings

Process Engineer

Joanna designs and optimizes drinking water systems and has led desktop, bench, full-scale and pipe loop corrosion control studies for Midwest utilities.

Mark ZIto

Trinnex Product Manager

Mark specializes in project planning, requirements analysis, stakeholder engagement and creating workflows that evolve into detailed systems.

Sandy Kutzing

Environmental Engineer

Sandy is CDM Smith's top strategist in the fight against lead in drinking water, optimizing corrosion control treatment and establishing lead service line replacement programs across the United States.

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