Getting the best out of ML with DataOps

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Presented by

Timm Grosser, BARC

About this talk

ML projects fail not because of great ideas, but often because of execution. The process for developing, operationalizing and running ML models seems too cumbersome and complicated. Therefore, ML models are often of limited use for automated decision making. Learn why this is the case and how DataOps can help. We will clarify questions in this webinar such as: What do we see in ML development & operations in companies today and what impact do these scattered processes have on the model benefit What does a seamless development, deployment and operating process looks like? Why should you think about DataOps? What are the biggest pitfalls in implementing these seamless processes?
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