Remove 2016 Remove Data mining Remove Metrics Remove Testing
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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., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

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

datapine

Whether you are a complete novice or a seasoned BI professional, you will find here some books on data analytics that will help you cultivate your understanding of this essential field. Before we delve deeper into the best books for data analytics, here are three big data insights to put their relevance and importance into perspective.

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). Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. After forming the X and y variables, we split the data into training and test sets. See Ribeiro et al.

Modeling 139