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For these reasons, publishing the data related to elections is obligatory for all EU member states under Directive 2003/98/EC on the re-use of public sector information and the Bulgarian Central Elections Committee (CEC) has released a complete export of every election database since 2011. The road ahead.
Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model. With those stakes and the long forecast horizon, we do not rely on a single statisticalmodel based on historical trends.
You know the markets shake and the accompanying Swine Flu epidemic of 2015 and 2016, the Japanese tsunami and the Thailand floods in 2011 that shook up the high-tech value chain quite a bit, the great financial crisis and the accompanying H1N1 outbreak in 2008-2009, MERS and SARS before that in 2003.
Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment.
In 2003, Oxford University professor Nick Bostrom asked what happens if you ask a smart AI to make as many paperclips as possible. In the long term, what we want is to have more leverage about the kinds of behaviors a model is producing.” For example, he says, an AI model can’t make a decision on a person’s access to healthcare.
5: What-if Analysis Models. allow for smart elements like modeling. Strategy 5: What-if Analysis Models. Building on the thought above, if you create exploratory environments it can be exceedingly accretive to decision-making if we build in what-if type models. 2: If Complex, Focus! 3: Venn Diagrams FTW! That’s the key.
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