Merge branch 'master' of github.com:CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

Author: CamDavidsonPilon

Chapter1_Introduction/Chapter1_Introduction.ipynb

@@ -135,7 +135,7 @@
       "\n",
       "We are interested in beliefs, which can be interpreted as probabilities by thinking Bayesian. We have a *prior* belief in event $A$, beliefs formed by previous information, e.g., our prior belief about bugs being in our code before performing tests.\n",
       "\n",
-      "Secondly, we observe our evidence. To continue our buggy-code example: if our code passes $X$ tests, we want to update our belief to incorporate this. We call this new belief the *posterior* probability. Updating our belief is done via the following equation, known as Bayes' Theorem, after it's discoverer Thomas Bayes:\n",
+      "Secondly, we observe our evidence. To continue our buggy-code example: if our code passes $X$ tests, we want to update our belief to incorporate this. We call this new belief the *posterior* probability. Updating our belief is done via the following equation, known as Bayes' Theorem, after its discoverer Thomas Bayes:\n",
       "\n",
       "\\begin{align}\n",
       " P( A | X ) = & \\frac{ P(X | A) P(A) } {P(X) } \\\\\\\\[5pt]\n",
@@ -1043,4 +1043,4 @@
    "metadata": {}
   }
  ]
-}
+}

README.md

@@ -1,4 +1,4 @@
-###Probabilistic Programming & Bayesian Methods for Hackers 
+#Bayesian Methods for Hackers
 #### *Using Python and PyMC*
 
 
@@ -49,7 +49,7 @@ Interactive notebooks + examples can be downloaded by cloning! )
     - Exploring a Kaggle dataset and the pitfalls of naive analysis
     - How to sort Reddit comments from best to worst (not as easy as you think)
 
-* [**Chapter 5: Would you rather loss 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)
+* [**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)
     The introduction of Loss functions and their (awesome) use in Bayesian methods.  Examples include:
     - Solving the Price is Right's Showdown
     - Optimizing financial predictions
@@ -121,8 +121,8 @@ Authors submit content or revisions using the GitHub interface.
 -  The current chapter list is not finalized. If you see something that is missing (MCMC, MAP, Bayesian networks, good prior choices, Potential classes etc.),
 feel free to start there. 
 -  Cleaning up Python code and making code more PyMC-esque.
--  Giving better explainations
--  Spelling/grammer mistakes
+-  Giving better explanations
+-  Spelling/grammar mistakes
 -  Suggestions
 -  Contributing to the IPython notebook styles.
 
@@ -165,6 +165,7 @@ Thanks to all our contributing authors, including (in chronological order):
 -  [ducky427](https://github.com/ducky427)
 -  [Pablo de Oliveira Castro](https://github.com/pablooliveira)
 -  [sergeyfogelson](https://github.com/sergeyfogelson)
+-  [Mattia Rigotti](http://neurotheory.columbia.edu/~mrigotti/)
 
 
 We would like to thank the Python community for building an amazing architecture. We would like to thank the