Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
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CamDavidsonPilon
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Update to pymc current version and add some Arviz content
How to solve this issue so the book can be used interactively in Jupyter? Adding "import cycler" changes nothing, even though I have cycler 0.11.0. Changing to "colors = ["#348ABD",...
The third cell will not work, it gives me: ``` In [3]: model.initial_values AttributeError: 'Model' object has no attribute 'initial_values' ``` This is a conda installation of pymc 5.10.3. I...
running the code for Stocks examples returns and error related to `pandas_datareader` as below: 
In the current stable **Matplotlib** version (3.7), `lw` (`linewidth`) should not be a string but float. [Reference](https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_linewidth). Fixed for Ch-1. Let me know if this format of PR is fine,...
Near the end of Chapter 2, in the section titled "Alternative PyMC model" a different model for the Privacy Algorithm is introduced. While I think I understand the equivalence of...
Hi. I'm new to TensorFlow and TensorFlow Probability. I'm running the examples in chapter 1, and when specifying the posterior sampler I get this error when running graph_sample_chain in line...
According to Turing.jl documentation: > Turing is a probabilistic programming system written entirely in Julia. It has an intuitive modelling syntax and supports a wide range of sampling-based inference algorithms....
Attempting to execute the following code in Ch 1 results in `TypeError: must be real number, not str`: ``` figsize(12.5, 4) colours = ["#348ABD", "#A60628"] prior = [0.20, 0.80] posterior...
line widths are incorrectly specified in Ch1_Introduction_PyMC_current.ipynb Changing strings to ints
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aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)