Structural Data Science Analyses vs Machine Learning and Back Again

Nick Mastronardi of local startup Polco will be presenting on the following ideas:

1. Most everyone's heard about "descriptive, predictive, prescriptive" and I think there's another after that "strategic - game theoretic" when there are few sophisticated players in a space that they've proven they have mapped the landscape of relationship among variables and not only choose an optimum prescription, but it must be in light of competittor's prescriptions. I'll talk through the progression from the perspective of time at Amazon, in Cyber Command, at Polco, and other environments I've seen.

2. Talk a little about the impact of increasingly big data on the balance between (structural data science / prescriptive analyses) vs. (descriptive analyses and Artificial Intelligence/Machine Learning). The trajectory of the impact is unidirectional. As data becomes bigger, we'll shift from structural analyses, to Machine Learning, to a balance between the two, back to more structural analyses. I'll give a couple examples from different work experiences.

Polco is a team of economists, policy experts, software engineers, and entrepreneurs dedicated to improving the way our political system works.

Cloudera will be providing the food for this event and Hortonworks will be providing the drinks.