Bayesian hierarchical time series with Prophet and PyMC3 - Matthijs Brouns | PyData Jeddah

Описание: When doing time-series modeling, you often end up in a situation where you want to make long-term predictions for multiple related time series. In this talk, we’ll see how we can combine the ideas behind Bayesian hierarchical models and Facebook's Prophet package to do exactly that.

Resources:

1. Presentation slides: https://drive.google.com/file/d/19ucW...

2. Timeseers code in Github:
https://github.com/MBrouns/timeseers

Timestamps:

0:00 - Intro
2:16 - About PyData Global Conference
3:32 - What is Prophet?
10:57 - Dealing with trends
14:21 - Linear trends in Prophet
16:19 - Linear trends in PyMC3 notebook
26:28 - Fourier seasonality
28:21 - Fourier seasonality in Prophet
29:09 - Fourier seasonality in PyMC3 notebook
35:26 - Prophet API
41:12 - Demo: Build a custom component using PyMC3 notebook
52:06 - Intro to Bayesian hierarchical models
1:08:00 - Q&A

Guest speaker:
Matthijs Brouns -   / mbrouns  

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