Probabilistic programming makes Bayesian inference accessible. It allows you to build interpretable models that quantify uncertainty and make use of both data and domain knowledge. In this report we show how to use probabilistic programming to build tools and products for more effective decision making.
Loan Officer Simulator
In Loan Officer Simulator you use graphs and metrics generated through a probabilistic model of loan repayments to decide which loans to approve and at what interest rate to approve them.
Probabilistic Real Estate predicts future real estate prices across the New York City boroughs. It enables you to input your housing budget and shows you the probability of finding properties in that price range across different neighborhoods and future time periods.
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