Mar

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2018

Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference

viphan 31 Mar 2018 03:19 LEARNING » e-book

Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference
Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference by Cameron Davidson-Pilon
English | 2 Oct. 2015 | ISBN: 0133902838 | 250 Pages | PDF (True) | 19.4 MB



Master Bayesian Inference through Practical Examples and Computation-Without Advanced Mathematical AnalysisBayesian 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 t...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 availableCameron 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.

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