Sandbox for reading and following the book "Think Bayes: Bayesian Statistics in Python", by Allen B. Downey (2012).
The purposes of this project are three:
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- To adapt the code of the book to my own style, and to make it more up-to-date and pythonic (e.g. use more standard libraries instead of those bizarre, custom-made libraries made by the author).
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- To add new (or edit) functions or classes so that the code looks more pedagogical, concise and intuitive.
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- To integrate both theory and code contained in the book under the same platform: the Jupyter Notebook. Ideally, as an interative book made of notebooks that could totally replace the need for the print book if one wishes to study it. The notebooks contain the essential theory covered in the book, not everything, so it is also ideal for "students in a hurry".
Warning: this is still a "work-in-progress" repository. It is meant as a supplemental tool (in addition to the book) for facilitating the learning experience of newcomers to the Bayesian framework.