[09x02] Essential Concepts for Bayesian Statistics, Probabilistic Programming and Turing.jl

Описание: Get a crash course in Bayesian Statistics, Bayes' Theorem, Bayesian Inference, Probabilistic Programming, Markov chain Monte Carlo (MCMC) Algorithms and the Turing.jl package.
Learn all of the essential concepts and terms.
This video refers to code from the last tutorial, Episode 901.

00:00 Intro
00:47 Motivation
02:14 What does Probability measure?
03:35 What is Bayesian Statistics?
04:21 What is Bayes' Theorem?
05:47 What is Bayesian Inference?
09:03 What is Probabilistic Programming?
10:45 What is an example of a Probabilistic Programming Workflow?
15:15 What is Markov chain Monte Carlo (MCMC)?
18:15 How should I interpret the Posterior Probability?
19:28 Conclusion
20:35 Outro

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Links for this tutorial
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Lambert, Ben. "A Student's Guide to Bayesian Statistics." YouTube playlist.
   • The syllabus covered by the book and YouTu...  

Code for this tutorial (GitHub) (code from Episode 901)
https://github.com/julia4ta/tutorials...

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Links for this series
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Link to Series 9 Playlist [Julia Probabilistic Programming for Beginners]
   • [09x01] How Much of Earth is Covered in Wa...  

Turing.jl Documentation
https://turinglang.org/stable/docs/us...

Turing.jl (GitHub)
https://github.com/TuringLang/Turing.jl

Turing.jl Website
https://turinglang.org/stable/

StatsPlots.jl Documentation
https://docs.juliaplots.org/latest/ge...

StatsPlots.jl (GitHub)
https://github.com/JuliaPlots/StatsPl...

Distributions.jl Documentation
https://juliastats.org/Distributions....

Distributions.jl (GitHub)
https://github.com/JuliaStats/Distrib...

The Julia Programming Language
https://julialang.org/
https://docs.julialang.org/en/v1/
   / @thejulialanguage  

VS Code
https://code.visualstudio.com/

Pluto.jl
https://plutojl.org/
https://github.com/fonsp/Pluto.jl

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   / @doggodotjl  

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