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From Bolts to Bots: How AI Is Fortifying the Automotive Industry

Smart Data Collective

The automotive market penetration of AI has increased by 100% since 2015. In July of 2015, two hackers managed to remotely take complete control of a Jeep Cherokee while it was driving on the highway. Utilizing advanced heuristics and AI modeling OEMs can simulate a multitude of conditions, fast-tracking these models using automation.

IoT 110
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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

Business analytics uses data analytics techniques, including data mining, statistical analysis, and predictive modeling, to drive better business decisions. Gartner defines business analytics as “solutions used to build analysis models and simulations to create scenarios, understand realities, and predict future states.”.

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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. But there are a few points I’d like to add, reiterate or amplify. The importance of AI and of recent AI advances differs greatly according to application or data category.

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Using random effects models in prediction problems

The Unofficial Google Data Science Blog

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. arXiv preprint arXiv:1506.04416 (2015). [6] Figure 2: Comparing custom Gibbs sampler vs. lmer running times.

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

Domino Data Lab

Skater uses different techniques depending on the type of the model (e.g. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. 2015) for additional details. PDPs for the bicycle count prediction model (Molnar, 2009). See Wei et al. Bahdanau, D.,

Modeling 139
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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.