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Title & Speakers Event
Claudia Stangarone – Data analyst @ GLS Studio , Helen FitzGerald – Data analyst

Claims in logistics, especially for lost parcels or delivery issues, can be a significant cost for companies. In this talk, we’ll present the framework and share some early results of a new feature within TrustCourier. This feature uses machine learning to predict and flag high-risk deliveries before they escalate into costly claims.

machine learning
Tamara Atanasoska – Open Source Software Engineer @ :probably..

Scikit-learn is a popular machine learning library. It currently has over 200 estimators ready to use for a vast array of use cases. What if you are working on something special that still hasn't found its way into the library? Scikit-learn offers a way to write new compatible estimators, which can be seamlessly integrated with the rest of the library. We will look into what an estimator is, what API that scikit-learn estimators have, reasons why you would like to implement your own and an example of how to. We will end with real-world examples of how other OSS projects use this for their needs.

scikit-learn Python
Stefanie Senger – Open source developer @ :probabl.

This talk will introduce scikit-learn users to the new API for metadata routing, a feature introduced in the recent releases and almost fully available since version 1.5 (released in May 2024).

Python scikit-learn open source
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