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Machine Learning Product Management: Lessons Learned

Domino Data Lab

I was fortunate to see an early iteration of Pete Skomoroch ’s ML product management presentation in November 2018. Pete Skomoroch, San Francisco, November 2018. Pete indicates, in both his November 2018 and Strata London talks, that ML requires a more experimental approach than traditional software engineering.

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Themes and Conferences per Pacoid, Episode 6

Domino Data Lab

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams. This is not that.

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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. 2018-06-21). Keep in mind that data science is fundamentally interdisciplinary.