Data Prep Failures
Automated data preparation systems often struggle with accurately binning data and establishing meaningful relationships between features. Despite their promise to enhance model building, these systems can produce misleading results, revealing critical gaps in their effectiveness. Identifying these failure patterns is essential for improving future automated approaches.In this clip
From this podcast

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
The New DBfication of ML/AI with Arun Kumar - #553
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