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@@ -101,6 +101,19 @@ The contents are updated synchronously as commits are made to the book. You can
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in these PDFs is not guarunteed to be the most recent content as the PDFs are only compiled periodically. Similarly, the book will not be
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interactive.
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Installation and configuration
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------
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If you would like to run the IPython notebooks locally, (option 1. above), you'll need to install the following:
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- IPython 0.13 is a requirement to view the ipynb files. It can be downloaded [here](http://ipython.org/ipython-doc/dev/install/index.html)
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- For Linux users, you should not have a problem installing Numpy, Scipy and PyMC. For Windows users, check out [pre-compiled versions](http://www.lfd.uci.edu/~gohlke/pythonlibs/) if you have difficulty.
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- In the styles/ directory are a number of files that are customized for the notebook.
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These are not only designed for the book, but they offer many improvements over the
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default settings of matplotlib and the IPython notebook. The in notebook style has not been finalized yet.
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- Currently the formatting of the style is not set, so try to follow what has been used so far, but inconsistencies are fine.
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Development
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------
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PDF, and increment the version of *Probabilistic Programming and Bayesian Methods for Hackers*.
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### How to contribute
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####What to contribute?
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- The current chapter list is not finalized. If you see something that is missing (MCMC, MAP, Bayesian networks, good prior choices, Potential classes etc.),
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feel free to start there.
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- Cleaning up Python code and making code more PyMC-esque.
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- Giving better explainations
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- Contributing to the IPython notebook styles.
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####Commiting
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- All commits are welcome, even if they are minor ;)
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- If you are unfamiliar with Github, you can email me contributions to the email below.
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Contributions and Thanks
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-----
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- [y-p](https://github.com/y-p)
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- [Ethan Brown](http://www.etano.net/)
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- [Jonathan Whitmore](http://jonathanwhitmore.com/)
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- [Mattia Rigotti](https://github.com/matrig)
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We would like to thank the Python community for building an amazing architecture. We would like to thank the
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### How to contribute
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####What to contribute?
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- The current chapter list is not finalized. If you see something that is missing (MCMC, MAP, Bayesian networks, good prior choices, Potential classes etc.),
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feel free to start there.
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- Cleaning up Python code and making code more PyMC-esque.
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- Giving better explainations
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- Contributing to the IPython notebook styles.
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####Installation and configuration
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- IPython 0.13 is a requirement to view the ipynb files. It can be downloaded [here](http://ipython.org/ipython-doc/dev/install/index.html)
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- For Linux users, you should not have a problem installing Numpy, Scipy and PyMC. For Windows users, check out [pre-compiled versions](http://www.lfd.uci.edu/~gohlke/pythonlibs/) if you have difficulty.
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- In the styles/ directory are a number of files that are customized for the notebook.
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These are not only designed for the book, but they offer many improvements over the
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default settings of matplotlib and the IPython notebook. The in notebook style has not been finalized yet.
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- Currently the formatting of the style is not set, so try to follow what has been used so far, but inconsistencies are fine.
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####Commiting
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- All commits are welcome, even if they are minor ;)
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- If you are unfamiliar with Github, you can email me contributions to the email below.
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####Contact
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Contact the main author, Cam Davidson-Pilon at [email protected] or [@cmrndp](https://twitter.com/cmrn_dp)
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