Mar 15–18, 2020
Catherine Nelson

Catherine Nelson
Senior Data Scientist, Concur Labs, SAP Concur

Website

Catherine Nelson is a Senior Data Scientist for Concur Labs at SAP Concur, where she explores innovative ways to use machine learning to improve the experience of a business traveller. She is particularly interested in privacy-preserving ML and applying deep learning to enterprise data. In her previous career as a geophysicist she studied ancient volcanoes and explored for oil in Greenland. Catherine has a PhD in geophysics from Durham University and a Masters of Earth Sciences from Oxford University.

Sessions

9:00am12:30pm Monday, March 16, 2020
Location: 210 F
Catherine Nelson (Concur Labs, SAP Concur), Hannes Hapke (Wunderbar.ai)
Most deep learning models don’t get analyzed, validated, and deployed. Catherine Nelson and Hannes Hapke explain the necessary steps to release machine learning models for real-world applications. You'll view an example project using the TensorFlow ecosystem, focusing on how to analyze models and deploy them efficiently. Read more.
11:00am11:40am Tuesday, March 17, 2020
Location: 210 C/G
Hannes Hapke (Wunderbar.ai), Catherine Nelson (Concur Labs, SAP Concur)
Measuring the machine learning model’s performance is key for every successful data science project. Therefore, model feedback loops are essential to capture feedback from users and to expand your model’s training dataset. This talk will introduce the concept of model feedback to you and guide you through a framework for increasing the ROI of your data science project. Read more.

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