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The saying garbage in is garbage out couldn’t be more true when it comes to data being fed into AI and ML models. In this podcast, hosts Kathleen Walch and Ron Schmelzer discuss the importance of data quality and why bad data is a main reason for AI project failure.
Show Notes:
CPMAI Methodology
CPMAI MethodologyIntro to CPMAI webinar
AI Today Podcast: AI Failure Series – Data Quantity & Data Understanding Issues
AI Today Podcast: AI Failure Series – ROI Misalignment
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