# CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

1 parent 739be38 commit 31308a73b9130df5574e3b2764ec80eb3e19d9dd committed Oct 15, 2016
Showing with 8 additions and 21 deletions.
1. +8 −21 Prologue/Prologue.ipynb
 @@ -48,51 +48,38 @@ "\n", "* [**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.\n", "\n", - "* [**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)\n", + "* [**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/Ch1_Introduction_PyMC3.ipynb)\n", " Introduction to the philosophy and practice of Bayesian methods and answering the question \"What is probabilistic programming?\" Examples include:\n", " - Inferring human behaviour changes from text message rates.\n", " \n", - "* [**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)\n", + "* [**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/Ch2_MorePyMC_PyMC3.ipynb)\n", " We explore modeling Bayesian problems using Python's PyMC library through examples. How do we create Bayesian models? Examples include:\n", " - Detecting the frequency of cheating students, while avoiding liars.\n", " - Calculating probabilities of the Challenger space-shuttle disaster.\n", " \n", - "* [**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)\n", + "* [**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/Ch3_IntroMCMC_PyMC3.ipynb)\n", " We discuss how MCMC operates and diagnostic tools. Examples include:\n", " - Bayesian clustering with mixture models\n", " \n", - "* [**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)\n", + "* [**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/Ch4_LawOfLargeNumbers_PyMC3.ipynb)\n", " We explore an incredibly useful, and dangerous, theorem: The Law of Large Numbers. Examples include:\n", " - Exploring a Kaggle dataset and the pitfalls of naive analysis\n", " - How to sort Reddit comments from best to worst (not as easy as you think)\n", " \n", - "* [**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/Chapter5.ipynb)\n", + "* [**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/Ch5_LossFunctions_PyMC3.ipynb)\n", " The introduction of Loss functions and their (awesome) use in Bayesian methods. Examples include:\n", " - Solving the Price is Right's Showdown\n", " - Optimizing financial predictions\n", " - Winning solution to the Kaggle Dark World's competition.\n", " \n", - "* [**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)\n", + "* [**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/Ch6_Priors_PyMC3.ipynb)\n", " Probably the most important chapter. We draw on expert opinions to answer questions. Examples include:\n", " - Multi-Armed Bandits and the Bayesian Bandit solution.\n", " - what is the relationship between data sample size and prior?\n", " - estimating financial unknowns using expert priors.\n", " \n", " We explore useful tips to be objective in analysis, and common pitfalls of priors. \n", - " \n", - "* **Chapter X1: Bayesian Markov Models**\n", - " \n", - "* **Chapter X2: Bayesian methods in Machine Learning** \n", - " We explore how to resolve the overfitting problem plus popular ML methods. Also included are probablistic explanations of Ridge Regression and LASSO Regression.\n", - " - Bayesian spam filtering plus *how to defeat Bayesian spam filtering*\n", - " - Tim Saliman's winning solution to Kaggle's *Don't Overfit* problem \n", - " \n", - "* **Chapter X3: More PyMC Hackery**\n", - " We explore the gritty details of PyMC. Examples include:\n", - " - Analysis on real-time GitHub repo stars and forks.\n", - "\n", - "* **Chapter X4: Troubleshooting and debugging**\n", - "\n", + " \n", " \n", "**More questions about PyMC?**\n", "Please post your modeling, convergence, or any other PyMC question on [cross-validated](http://stats.stackexchange.com/), the statistics stack-exchange.\n", @@ -291,7 +278,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", - "version": "2.7.10" + "version": "2.7.11" } }, "nbformat": 4,