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What you need to know about product management for AI

O'Reilly on Data

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. To be clear, we are not saying that data can or should be used indiscriminately, without concern for legal compliance, customer privacy, bias, and other ethical issues.).

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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

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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. Keep in mind that data science is fundamentally interdisciplinary. Let’s look through some antidotes.

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Improving Multi-tenancy with Virtual Private Clusters

Cloudera

The typical Cloudera Enterprise Data Hub Cluster starts with a few dozen nodes in the customer’s datacenter hosting a variety of distributed services. Over time, workloads start processing more data, tenants start onboarding more workloads, and administrators (admins) start onboarding more tenants.

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Digital Analytics + Marketing Career Advice: Your Now, Next, Long Plan

Occam's Razor

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. The Future of Life Institute hosted a conference in Asilomar in Jan 2017 with just such a purpose. This reality powers my impostor syndrome, and (yet?)

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