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Merge pull request CamDavidsonPilon#240 from CamDavidsonPilon/try-this-again
Rename ipynb to reflect chapter and add a naive pdf converter
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Chapter1_Introduction/README.md

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Chapter 1: Introduction to Bayesian Methods
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===========
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter1_Introduction/Chapter1_Introduction.ipynb)
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter1_Introduction/Chapter1.ipynb)
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Chapter2_MorePyMC/README.md

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Chapter 2: A little more on PyMC
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=================================
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter2_MorePyMC/MorePyMC.ipynb)
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter2_MorePyMC/Chapter2.ipynb)
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Chapter3_MCMC/README.md

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Chapter 3: Opening the black box of MCMC (Markov Chain Monte Carlo)
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==================================================================
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter3_MCMC/IntroMCMC.ipynb)
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter3_MCMC/Chapter3.ipynb)
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Chapter 4: The Greatest Theorem Never Told
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====
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter4_TheGreatestTheoremNeverTold/LawOfLargeNumbers.ipynb)
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter4_TheGreatestTheoremNeverTold/Chapter4.ipynb)

Chapter5_LossFunctions/README.md

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Chapter 5: Would you rather lose an arm or a leg?
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter5_LossFunctions/LossFunctions.ipynb)
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter5_LossFunctions/Chapter5.ipynb)
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Chapter6_Priorities/README.md

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Chapter 6: Getting our priorities straight
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===========
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter6_Priorities/Priors.ipynb)
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### [Read it online here](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter6_Priorities/Chapter6.ipynb)

README.md

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* [**Prologue:**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Prologue/Prologue.ipynb) Why we do it.
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* [**Chapter 1: Introduction to Bayesian Methods**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter1_Introduction/Chapter1_Introduction.ipynb)
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* [**Chapter 1: Introduction to Bayesian Methods**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter1_Introduction/Chapter1.ipynb)
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Introduction to the philosophy and practice of Bayesian methods and answering the question, "What is probabilistic programming?" Examples include:
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- Inferring human behaviour changes from text message rates
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* [**Chapter 2: A little more on PyMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter2_MorePyMC/MorePyMC.ipynb)
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* [**Chapter 2: A little more on PyMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter2_MorePyMC/Chapter2.ipynb)
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We explore modeling Bayesian problems using Python's PyMC library through examples. How do we create Bayesian models? Examples include:
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- Detecting the frequency of cheating students, while avoiding liars
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- Calculating probabilities of the Challenger space-shuttle disaster
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* [**Chapter 3: Opening the Black Box of MCMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter3_MCMC/IntroMCMC.ipynb)
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* [**Chapter 3: Opening the Black Box of MCMC**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter3_MCMC/Chapter3.ipynb)
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We discuss how MCMC operates and diagnostic tools. Examples include:
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- Bayesian clustering with mixture models
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* [**Chapter 4: The Greatest Theorem Never Told**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter4_TheGreatestTheoremNeverTold/LawOfLargeNumbers.ipynb)
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* [**Chapter 4: The Greatest Theorem Never Told**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter4_TheGreatestTheoremNeverTold/Chapter4.ipynb)
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We explore an incredibly useful, and dangerous, theorem: The Law of Large Numbers. Examples include:
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- Exploring a Kaggle dataset and the pitfalls of naive analysis
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- How to sort Reddit comments from best to worst (not as easy as you think)
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* [**Chapter 5: Would you rather lose an arm or a leg?**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter5_LossFunctions/LossFunctions.ipynb)
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* [**Chapter 5: Would you rather lose an arm or a leg?**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter5_LossFunctions/Chapter5.ipynb)
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The introduction of loss functions and their (awesome) use in Bayesian methods. Examples include:
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- Solving the *Price is Right*'s Showdown
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- Optimizing financial predictions
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- Winning solution to the Kaggle Dark World's competition
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* [**Chapter 6: Getting our *prior*-ities straight**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter6_Priorities/Priors.ipynb)
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* [**Chapter 6: Getting our *prior*-ities straight**](http://nbviewer.ipython.org/urls/raw.github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter6_Priorities/Chapter6.ipynb)
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Probably the most important chapter. We draw on expert opinions to answer questions. Examples include:
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- Multi-Armed Bandits and the Bayesian Bandit solution.
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- What is the relationship between data sample size and prior?

to_latex_pdf.sh

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gcd Chapter1_Introduction/ && ipython nbconvert Chapter1.ipynb --to latex --post PDF --template article
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cd ../Chapter2_MorePyMC/ && ipython nbconvert Chapter2.ipynb --to latex --post PDF --template article
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cd ../Chapter3_MCMC/ && ipython nbconvert Chapter3.ipynb --to latex --post PDF --template article
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cd ../Chapter4_TheGreatestTheoremNeverTold/ && ipython nbconvert Chapter4.ipynb --to latex --post PDF --template article
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cd ../Chapter5_LossFunctions/ && ipython nbconvert Chapter5.ipynb --to latex --post PDF --template article
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cd ../Chapter6_Priorities/ && ipython nbconvert Chapter6.ipynb --to latex --post PDF --template article

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