Probabilistic Programming Primer by Peadar Coyle

Probabilistic Programming Primer

A step by step guide to Probabilistic Programming

Overview

Probabilistic Programming is one of those tricky areas of Machine Learning and Applied Statistics.
In this course join Peadar Coyle a core-developer of PyMC3 as he takes you through
- What PyMC3 is for
- What MCMC is and why should I care
- How to know enough theano to not be scared by it
- How to diagnose things like model convergence and figure out if your model is good or not
- An introduction to Multi-level models or Bayesian Stats super sauce

FAQs

What is the target audience with this course?

My target audience is people with some statistics background or machine learning background. If you know some Python (or another suitable language like Scala, R, Java) and some Machine Learning you should be fine. 

My aim is to present things in a 'hacker' friendly way. 

Does this course have an expiry date?

No, the price gets you lifetime access to the course, especially as I add more content. It's a one-time-fee. 

How much will this course cost?

The course will be fixed price cost for 150 dollars - that'll include several hours of videos, notebooks and all other content we add to this product over the lifetime of the product. 

Learn how to wield Bayesian Stats in industry without going to grad school!

I'm Peadar Coyle a core developer of a Probabilistic Programming/Bayesian stats library in Python - PyMC3. 

I'll take beginners and not-so-beginners on a journey to learn some actionable skills and how to apply Bayesian Statistics in your day to day work.