Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference Using Python and PyMC

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.

Pages : 256 pages
Size : PDF Files
File type : pdf
Downloads: 117
Created: 2020-08-28
License: MIT License
Author(s): Cameron Davidson-Pilon
Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference Using Python and PyMC

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