Anne Cocos' podcast interview on location ML

Iggy's head of data science Anne Cocos recently sat down to discuss Iggy and location ML on the ML Ops Community podcast.

Tune in to hear Anne discuss: 

  • Motivations for iggy, based on our CEO Lindsay's experience as a data scientist at Airbnb,
  • How we build our core/canonical datasets,
  • Lessons learned from ingesting massive datasets with complex geometries (I.e. FEMA flood data),
  • How iggy can help w health outcomes,
  • Navigating the pre-PMF journey,
  • Why Anne thinks machine learning on geospatial data is particularly cool.

We hope you enjoy it! Reach out on Twitter or email w comments or questions.

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Meet Team Iggy: Lindsay Pettingill

As I was finishing my PhD, I did Insight Data Science and got hired at Airbnb where I hoped to use geospatial data to work on host growth or something. I was working on the host team as a Data Scientist and I realized that we didn't have any concept of the “context” of our listings… we knew a lot about the listing and its specific characteristics but we didn't really have a way to understand what was nearby. That matters because if you know what’s nearby you can market listings differently (which is sort of what Airbnb is (finally) doing w Categories), you can price more accurately, and you can drastically improve search. That became really compelling to me. I tried to work on an internal project there, but it didn't get a lot of support. So eventually, I decided to leave Airbnb and start Iggy to solve this challenge.