Remove 2019 Remove Experimentation Remove ROI Remove Statistics
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What you need to know about product management for AI

O'Reilly on Data

All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. What do you recommend to organizations to harness this but also show a solid ROI? What are you most looking forward to about CDAOI Insurance 2019?

Insurance 150
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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

So much work in machine learning – either on the academic side which is focused on publishing papers or the industry side which is focused on ROI – tends to emphasize: How much predictive power (precision, recall) does the model have? Use of influence functions goes back to the 1970s in robust statistics.