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 ;)
Going through chapter 5 I found it weird that there was no implementation of the optimal solution for the Dark Worlds problem, i.e. find the best guess that minimizes the...
@CamDavidsonPilon please consider this PR to fix the bug in chapter 4, the score is not calculated correctly for multiple halos
[flake8](http://flake8.pycqa.org) testing of https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers on Python 3.7.0 $ __flake8 . --count --select=E901,E999,F821,F822,F823 --show-source --statistics__ ``` ./Chapter3_MCMC/github_pull.py:78:28: E999 SyntaxError: invalid syntax print " -------------- " ^ ./sandbox/Chapter10_/github_datapull.py:16:55: E999 SyntaxError: invalid syntax...
Hello, Enoying this superb book so far. When trying to build the python environment (on ubuntu 18.04) ala: ``` mkvirtualenv bayes pip install -r requirements.txt ``` I received several cryptic...
When I run the notebook for Chapter 2 on pymc2, it fails with the error below. It looks like current implementation is not compatible with numpy boolean subtract. python version:...
The original plot gives the following error: ValueError: x and y must have same first dimension, but have shapes (50000,) and (125000,) have change numpy arange so the dimensions are...
While using this piece of code !!! ### Mysterious code to be explained in Chapter 3. with model: step = pm.Metropolis() trace = pm.sample(10000, tune=5000,step=step) Gives an error !! ValueError:...
I think that there are 2 problems with the strategies adopted in chapter 5: 1) The text suggests that strategies 4 and 5 are different and will be applied. The...
I became quite confused by the **Algorithms to perform MCMC** section. The issue is that steps 3-4: "*3. Accept/Reject the new position based on the position's adherence to the data...
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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 ;)