Probabilistic programming systems make it easier to learn from data. Fast Forward Lab's Mike Lee Williams demos a novel no-math-required way to make one.
You have two web site designs. Which one best converts customers? Choose wrong and you're out a million bucks. See how Mike Lee William's Approximate Bayesian Computation (ABC) inference machine transforms a trove of typically imperfect and incomplete data into an A/B choice you can live with.
What you will learn:
- Build a probabilistic programming system from scratch using ABC and basic Python
- Understand ABC: A no-math-required, easy-to-code algorithm that performs Bayesian inference
- Explore three highly attractive advantages to the Bayesian approach