Introduction to Bayesian Analysis in Python
Introduction to Bayesian Analysis in Python
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 10M | 231 MB
Genre: eLearning | Language: English
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 10M | 231 MB
Genre: eLearning | Language: English
Bayesian statistics is an effective tool for solving some inference problems when the available sample is too small for more complex statistical analysis to be applied. This course teaches the main concepts of Bayesian data analysis. It focuses on how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, model checking, and validation.
The course introduces the framework of Bayesian Analysis. Complex mathematical theory will be sidestepped in favor of a more pragmatic approach, featuring computational methods implemented in the Python library PyMC3. We present several instances of analysis scenarios.
All the codes of the course are uploaded on the Github repository: https://github.com/PacktPublishing/-Introduction-to-Bayesian-Analysis-in-Python
Introduction to Bayesian Analysis in Python
