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Transforming Credit and Collection with Predictive Analytics

BizAcuity

According to a Federal Bank report, more than $600 billion of household debt in the U.S. is delinquent as of June 30th, 2017. By clubbing various techniques like data mining, machine learning, artificial intelligence and statistical modelling, it makes predictions about events in the future.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. e-handbook of statistical methods: Summary tables of useful fractional factorial designs , 2018 [3] Ulrike Groemping. Hedayat, N.J.A.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.