Bay Area Probabilistic Programming Meetup

Is probabilistic programming and Bayesian reasoning algorithms the next big thing in machine learning? The idea behind the probabilistic programming to machine learning is that the model of the data can be separated from the algorithms that do inference on the model. The allows you to devote your energy to building models tailored to your decision problem, as opposed to constraining your problem so it works with some machine learning tool. This idea opens machine learning to domain experts. Indeed, probabilistic programming grew out of probabilistic graphical models, which revolutionized AI by enabling expert knowledge to be built into graphs powered by Bayesian inference.