Data Debt Insights
Exploring the challenges of large datasets, the importance of understanding data debt emerges as a crucial topic. Insights reveal that feelings of unease regarding model performance can serve as a proxy for technical debt. Key questions about system modifications and the frequency of outages highlight the need for robust tools and techniques in machine learning environments.In this clip
From this podcast

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Data Debt in Machine Learning with D. Sculley - #574
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