O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself.

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Management Machine Learning Experimentation Metrics 339

Sisense

DECEMBER 13, 2021

Luckily, there are intelligent and scalable ways institutions can access and make sense of their data, allowing them to spot trends and extract insights that drive innovation and inspire creative solutions. Many financial institutions face common challenges when it comes to turning their big data sets into actionable business intelligence.

Data-driven 59

Data-driven IT Business Intelligence Cost-Benefit 59

Domino Data Lab

JUNE 2, 2019

She had much to say to leaders of data science teams, coming from perspectives of data engineering at scale. And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. Being model-driven is like using GPS.”. “If

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110