Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Bayesian Analysis with Python

You're reading from   Bayesian Analysis with Python Unleash the power and flexibility of the Bayesian framework

Arrow left icon
Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785883804
Length 282 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Osvaldo Martin Osvaldo Martin
Author Profile Icon Osvaldo Martin
Osvaldo Martin
Arrow right icon
View More author details
Toc

Table of Contents (10) Chapters Close

Preface 1. Thinking Probabilistically - A Bayesian Inference Primer FREE CHAPTER 2. Programming Probabilistically – A PyMC3 Primer 3. Juggling with Multi-Parametric and Hierarchical Models 4. Understanding and Predicting Data with Linear Regression Models 5. Classifying Outcomes with Logistic Regression 6. Model Comparison 7. Mixture Models 8. Gaussian Processes Index

Exercises

We don't know if the brain really works in a Bayesian way, in an approximate Bayesian fashion, or maybe some evolutionary (more or less) optimized heuristics. Nevertheless, we know that we learn by exposing ourselves to data, examples, and exercises. Although you may disagree with this statement given our record as a species on wars, economic-systems that prioritize profit and not people's wellbeing, and other atrocities. Anyway, I strongly recommend you to do the proposed exercises at the end of each chapter:

  1. Modify the code that generated figure 3 in order to add a dotted vertical line showing the observed rate head/(number of tosses), compare the location of this line to the mode of the posteriors in each subplot.
  2. Try reploting figure 3 using other priors (beta_params) and other data (trials and data).
  3. Read about Cromwell's rule at Wikipedia https://en.wikipedia.org/wiki/Cromwell%27s_rule.
  4. Explore different parameters for the Gaussian, binomial and beta plots. Alternatively, you may want to plot a single distribution instead of a grid of distributions.
  5. Read about probabilities and the Dutch book at Wikipedia https://en.wikipedia.org/wiki/Dutch_book.
You have been reading a chapter from
Bayesian Analysis with Python
Published in: Nov 2016
Publisher: Packt
ISBN-13: 9781785883804
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image