Introduction to Probabilistic Machine Learning with Stan


Machine Learning has gone mainstream and now powers several real world applications like autonomous vehicles at Uber & Tesla, recommendation engines on Amazon & Netflix, and much more. In this meetup, I introduced probabilistic machine learning and probabilistic programming with Stan. I discussed the basics of machine learning from a probabilistic/Bayesian perspective and contrasted it with traditional/algorithmic machine learning. I also discussed how to build probabilistic models in computer code using a new exciting programming paradigm called Probabilistic Programming (PP). Particularly I used Stan (within R), a PP language, to build models ranging from simple generalized linear models to complex hierarchical models and nonparametric models for machine learning.

Las Vegas, Nevada


The following software tools are required to run the demo(s):

  1. R + RStudio:- Follow this link to install R. Also install RStudio.
  2. rstan:- Follow this link to install rstan.
  3. bayesplot:- Follow this link to install bayesplot