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, it’s 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 , you’ll learn how Dataiku can help you to:-
- Increase agility and solve difficulties in handoffs between business, data scientists and IT.
- Make your models trusted from the get-go
- Apply model control & approvals to enable, not disable your AI projects
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. She’s 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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