Probabilistic Thinking with James "JD" Long

Our show host and Senior Content Advisor, Q McCallum, has been thinking a lot about what he calls "moving beyond the point estimate" in ML modeling. That usually starts with seeing the world in terms of statistical distributions, and running simulations to get a more robust picture of a model's results. When he had questions, he reached out to his old friend James "JD" Long for answers. James is a self-described "agricultural economist, quant, stochastic modeler, and cocktail party host" who does a lot of work in R, Python, and AWS. Through his work in the reinsurance field he has developed deep knowledge of simulations and probabilistic thinking, as well as an ability to explain these topics in plain language.

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The official podcast of Data Science Salon. We interview top and rising luminaries in data science, machine learning, and AI on the trends and business use cases that are propelling the field forward. The Data Science Salon series is a unique vertical focused conference which brings together specialists face-to-face to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere with food, great coffee, and entertainment.