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According to McKinsey, by building ML into processes, leading organisations are increasing process efficiency by 30% or more while also increasing revenues by 5% to 10%. However, itโs not that simple. Several blockers prevent organisations from overcoming the difficulties encountered when industrialising AI. As a result, it can take up to nine months for teams to go from the Proof-of-Concept stage to the Production stage. In this context, how do you remove frictions from your MLOps process and make your model processes trusted, agile & controlled, so that you can finally deliver more value from your model & analytics faster? In this session, with @CatalinaHerrera , youโll learn how Dataiku can help you to:-
About our speaker
With a passion for data and analytics, @CatalinaHerrera has spent her entire career helping the industry push beyond digitalization to business transformation. Sheโs held educational and technical positions, worked with state-of-the-art technology solutions across multiple industry verticals, and served as a data scientist and SaaS technology evangelist. In 2020, her influence in the AI community in Texas resulted in her being recognized as one of the top 30 women in Artificial Intelligence Advancement
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