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Once a machine learning model is trained and validated, it often feels like a major milestone has been achieved. In reality, it’s more like the first lap in a relay race. Deploying ML to production bears many similarities to a typical software release process, but brings several novel challenges like failing to generalize as expected or model drift.
AI Quality management is the biggest challenge in AI today. In this episode, I interview Anupam Datta, the co-founder at TruEra. TruEra has a solution aimed at helping with AI performance, monitoring, and model explainability. We talk about some of the challenges of modern machine learning deployment in production and how companies are succeeding with ML Ops.
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The post Responsibly Deploy AI in Production with Anupam Datta appeared first on Software Engineering Daily.