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The Business Intelligence Market – What’s Old is New

In(tegrate) the Clouds

As the data visualization, big data, Hadoop, Spark and self-service hype gives way to IoT, AI and Machine Learning, I dug up an old parody post on the business intelligence market circa 2007-2009 when cloud analytics was just a disruptive idea. Ad hoc query, data mining, information I’m still not finding.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

The problem with this approach is that in highly imbalanced sets it can easily lead to a situation where most of the data has to be discarded, and it has been firmly established that when it comes to machine learning data should not be easily thrown out (Banko and Brill, 2001; Halevy et al., The unreasonable effectiveness of data.

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

Domino Data Lab

Skater provides a wide range of algorithms that can be used for visual interpretation (e.g. Partial Dependence Plot is another visual method, which is model agnostic and can be successfully used to gain insights into the inner workings of a black-box model like a deep ANN. PDPs for the bicycle count prediction model (Molnar, 2009).

Modeling 139
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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

A 2009 investigative survey by Dr. Daniele Fanelli from The University of Edinburgh found that 33.7% of scientists surveyed admitted to questionable research practices, including modifying results to improve outcomes, subjective data interpretation, withholding analytical details, and dropping observations because of gut feelings….