Remove 2016 Remove Data mining Remove Measurement Remove Risk
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

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Unlock The Power of Your Data With These 19 Big Data & Data Analytics Books

datapine

An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”. If we had to pick one book for an absolute newbie to the field of Data Science to read, it would be this one.

Big Data 263
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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

2016) for an example of this technique (LIME). For this demo we’ll use the freely available Statlog (German Credit Data) Data Set, which can be downloaded from Kaggle. This dataset classifies customers based on a set of attributes into two credit risk groups – good or bad. See Ribeiro et al. See Wei et al.

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

datapine

These controlling measures are essential and should be part of any experiment or survey – unfortunately, that isn’t always the case. Drinking tea increases diabetes by 50%, and baldness raises the cardiovascular disease risk up to 70%! In 2012, the global mean temperature was measured at 58.2 So, can statistics be manipulated?