Bayesian Statistics MOOC by Coursera - Solutions in Python
This repository is a Python implementation of the different algorithms and problems proposed in the the courses Bayesian Statistics: From Concept to Data Analysis, Bayesian Statistics: Techniques and Models and Bayesian Statistics: Mixture Models offered by the University of California Santa Cruz in Coursera.
The main idea is to provide a Python-based implementation in order to enable people who is not familiarized with R to play and learn Bayesian Statistics.
Note: Quizes and projects are not shared in this repository, only examples given within the lectures. All the text, equations and explanations were directly taken from the course.
The following table of content shows the different algorithms implemented in this repository.
To start using this repository, run the following command and install the needed dependencies.
pip install -r requirements.txt
Open jupyter notebook in your favorite IDE and enjoy!