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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. Skater uses different techniques depending on the type of the model (e.g. 2015) for additional details. Bahdanau, D.,

Modeling 139
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Notes on artificial intelligence, December 2017

DMBS2

Most of my comments about artificial intelligence in December, 2015 still hold true. Predictive modeling is a huge deal in customer-relationship apps. Voice interaction is already revolutionary in certain niches (e.g. But there are a few points I’d like to add, reiterate or amplify.

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Data Science at The New York Times

Domino Data Lab

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

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Using random effects models in prediction problems

The Unofficial Google Data Science Blog

Column "a" is an advertiser id, "b" is a web site, and "c" is the 'interaction' of columns "a" and "b". $y$ We have many routine analyses for which the sparsity pattern is closer to the nested case and lme4 scales very well; however, our prediction models tend to have input data that looks like the simulation on the right.

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AI is key player in Texas Rangers’ winning formula

CIO Business Intelligence

In 2015, Major League Baseball revolutionized a sport already known for its sophisticated use of data with MLB Statcast, a tracking technology that collects enormous amounts of game data. We were the go-to guys for any ML or predictive modeling at that time, but looking back it was very primitive.”