How to Train a Click Through Ratio Model

We show users lots of diffrnt items that they could potentially click on. Tey'r only probly can click handful, you know, if any. And we call it our click ther model. If the thing ou're tring to predict only happens one and a hundred times a model caun do very well if it just predicts zero. But sometimes it does matter. So io, maybe let say ond jump in abut when it does Matter.

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MLOps Coffee Sessions #78 with Erica Greene and Seoyoon Park, Calibration for ML at Etsy - apply() special.

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// Abstract
This is a special conversation about Machine Learning calibration at Etsy. Demetrios sat down with Erica Greene and Seoyoon Park to hear about how they implemented Calibration into the Etsy Machine Learning workflow.
The conversation is a pre-chat with these two before their presentation at the apply() conference on February 10th.
Register here: applyconf.com

// Bio
Erica Geen
Erica is an engineering manager with a background in machine learning. She's passionate about developing programs and policies that support women and other underrepresented groups in technology.

Seoyoon Park
Backend software engineer and aspiring software architect interested in producing scalable, performant, and fault-tolerant applications by keeping up to date with best practices and industry standards. Seoyoon strives to better himself and his peers by advocating for frequent knowledge transfers and promoting a culture of continuous learning. Constantly looking for opportunities to grow as a developer and become a leader of the industry.

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Erica on LinkedIn: https://www.linkedin.com/in/ericagreene/
Connect with Seoyoon on LinkedIn: https://www.linkedin.com/in/seoyoonpark/

Timestamps:

[00:00] Quick notes

[00:47] Introduction to Erica Greene and Seoyoon Park

[02:37] Looking for an editor

[04:23] Seoyoon Park's background

[06:01] Erica Greene's background

[08:07] Seoyoon's transition to ML

[10:25] Erica's take as team manager

[11:58] Additional points from Seoyoon

[13:17] Early wins in ML

[15:41] Seoyoon's start in ML