People of AI
Rocks, data science, and breaking into Machine Learning
Apr 6, 2023
Meet Catherine Nelson, a geophysicist turned Principal Data Scientist at SAP Concur, discussing her journey and insights into building machine learning pipelines. She emphasizes the importance of data preparation and training, model interpretability for ethical ML, and the value of diverse backgrounds in the field. The podcast also covers topics such as data quality, auditing, and favorite AI-related books.
23:59
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Quick takeaways
- Preparing and training data is crucial for building machine learning pipelines.
- Model interpretability is essential for ethical machine learning usage and user trust.
Deep dives
Transition from Geoscience to Data Science
Katherine shares her journey transitioning from geoscience, where she studied ancient volcanoes and oil exploration, to data science. After finding limited job opportunities in geology, she discovered data science through LinkedIn in 2014, leading her to upskill in Python and machine learning. By engaging in personal projects and leveraging TensorFlow for image rating, she secured her first data science position at SAP Concur.
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