| Sumario: | This event introduces advanced math for business people — "just enough" to take advantage of open source frameworks — including graph theory, abstract algebra, optimization, bayesian statistics, and more advanced areas of linear algebra. These are needed for supply chain optimization, pricing models, and anti-fraud, especially given the increased data rates coming from the Internet of Things. Paco Nathan discusses how to: Develop themes within the material to highlight a computational thinking approach for Big Data Decompose a complex problem into smaller solvable problems Leverage pattern recognition to identify when a known approach can be leveraged Abstract from those patterns into generalizations as strategies Articulate strategies as algorithms — general recipes for how to handle complex problems He will also focus on morsels of advanced math, tying each new concept to a concrete business use case, showing brief code examples in Python.
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