Introduction to PyMC3 for Bayesian Modeling and Inference
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Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Beginner
- Deadline
- Flexible
- Duration
- 12 hours
- Certificate
- Paid Certificate Available
- Course author
- Dr. Srijith Rajamohan
-
1. The PyMC3/ArViz framework for Bayesian modeling and inference
2. Build real-world models using PyMC3 and assess the quality of your models
Description
The objective of this course is to introduce PyMC3 for Bayesian Modeling and Inference, The attendees will start off by learning the the basics of PyMC3 and learn how to perform scalable inference for a variety of problems. This will be the final course in a specialization of three courses .Python and Jupyter notebooks will be used throughout this course to illustrate and perform Bayesian modeling with PyMC3.. The course website is located at https://sjster.github.io/introduction_to_computational_statistics/docs/index.html. The course notebooks can be downloaded from this website by following the instructions on page https://sjster.github.io/introduction_to_computational_statistics/docs/getting_started.html.The instructor for this course will be Dr. Srijith Rajamohan.
