Talk Abstract
In the mobile game Pokemon GO, players can rarely encounter “shiny” Pokemon. The exact appearance rates are unknown. But by using Bayesian inference and PyMC3, we can model different species’ shiny rates. In this beginner-level tutorial, we will introduce fundamental principles at the heart of Bayesian modeling; then we will apply them to develop PyMC3 models that can answer questions about Pokemon GO.
| Tushar Chandra | Twitter @threeshar |
GitHub tuchandra |
Personal website |
Talk
Tushar Chandra
Tushar is a senior data scientist at Nielsen Global Media in Chicago. At Nielsen, he works on developing Bayesian models for next-generation audience measurement. He loves cats (living with two, Luna and Ruby), chai, and college football. This is his first conference talk!
This is a PyMCon 2020 talk
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