Bayesian Methods for Hackers

Bayesian Methods for Hackers
Author :
Publisher : Addison-Wesley Professional
Total Pages : 551
Release :
ISBN-10 : 9780133902921
ISBN-13 : 0133902927
Rating : 4/5 (927 Downloads)

Book Synopsis Bayesian Methods for Hackers by : Cameron Davidson-Pilon

Download or read book Bayesian Methods for Hackers written by Cameron Davidson-Pilon and published by Addison-Wesley Professional. This book was released on 2015-09-30 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.


Bayesian Methods for Hackers Related Books

Bayesian Methods for Hackers
Language: en
Pages: 551
Authors: Cameron Davidson-Pilon
Categories: Computers
Type: BOOK - Published: 2015-09-30 - Publisher: Addison-Wesley Professional

DOWNLOAD EBOOK

Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural a
Bayesian Methods for Hackers
Language: en
Pages: 0
Authors: Cameron Davidson-Pilon
Categories: Bayesian statistical decision theory
Type: BOOK - Published: 2016 - Publisher: Addison-Wesley Professional

DOWNLOAD EBOOK

The next generation of problems will not have deterministic solutions - the solutions will be statistical that rely on mountains, or mounds, of data. Bayesian m
Bayesian Methods for Hackers
Language: en
Pages:
Authors: Cameron Davidson-Pilon
Categories: Bayesian statistical decision theory
Type: BOOK - Published: 2016 - Publisher:

DOWNLOAD EBOOK

Bayesian Reasoning and Machine Learning
Language: en
Pages: 739
Authors: David Barber
Categories: Computers
Type: BOOK - Published: 2012-02-02 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.
Practical Probabilistic Programming
Language: en
Pages: 650
Authors: Avi Pfeffer
Categories: Computers
Type: BOOK - Published: 2016-03-29 - Publisher: Simon and Schuster

DOWNLOAD EBOOK

Summary Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you'll learn how to use the PP paradigm to mo