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

Domino Data Lab

2015) for additional details. The surrogate model is often a simple linear model or a decision tree, which are innately interpretable, so the data collected from the perturbations and the corresponding class output can provide a good indication on what influences the model’s decision. See Wei et al. 1135–1144, ACM, 2016.

Modeling 139
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MLOps and the evolution of data science

IBM Big Data Hub

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

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Mobile Marketing 2015: Rethink Customer Acquisition, Intent Targeting

Occam's Razor

Two companies, Skullcandy and TripIt, delivering on four amazing outcomes that inspire us to set the bar significantly higher for our mobile efforts in 2015 (or sooner!). I'm sure you are impressed at the data mining and intent targeting efforts of TripIt. That is what all marketing in 2015 will look like.

Marketing 144
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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

In this post we will look mobile sites first, both data collection and analysis, and then mobile applications. Upsight (nee Kontagent) provides mobile app analytics, with a pinch of advanced segmentation (including sweet cohort analysis ) and big data mining thrown in for good measure. Tag your mobile website.

Metrics 141
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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity! Misleading statistics refers to the misuse of numerical data either intentionally or by error. 29, 2015, Republicans from the U.S. 3) Data fishing.