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By most estimates, fewer than 20% of machine learning projects make it past the initial pilot stage—a staggering stat in and of itself.

So, in order to succeed with ML, data scientists must work closely with developers, line of business, and IT operations teams to plan for future needs and model success to help justify costs. But how?

Tune into this webcast to explore the biggest challenges faced when implementing a machine learning project, where teams get tripped up, and how to avoid these roadblocks.

The recording will also cover advice for IT leaders about how to scale and support a machine learning project as it grows.

Vendor:

Hewlett Packard Enterprise

Premiered:

Mar 11, 2021

Format:

Multimedia

Type:

Webcast