35 - Normal prior and likelihood - posterior predictive distribution
This video provides a derivation of the normal posterior predictive distribution for the case of a normal prior distribution and likelihood. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4o
From playlist Bayesian statistics: a comprehensive course
29 - Posterior predictive distribution: example Disease
This video provides an introduction to the concept of posterior predictive distributions, using the example of disease prevalence in a population. Here we consider the case of a beta prior and binomial likelihood; resulting in a beta-binomial posterior. If you are interested in seeing mo
From playlist Bayesian statistics: a comprehensive course
(ML 7.9) Posterior distribution for univariate Gaussian (part 1)
Computing the posterior distribution for the mean of the univariate Gaussian, with a Gaussian prior (assuming known prior mean, and known variances). The posterior is Gaussian, showing that the Gaussian is a conjugate prior for the mean of a Gaussian.
From playlist Machine Learning
(ML 7.10) Posterior distribution for univariate Gaussian (part 2)
Computing the posterior distribution for the mean of the univariate Gaussian, with a Gaussian prior (assuming known prior mean, and known variances). The posterior is Gaussian, showing that the Gaussian is a conjugate prior for the mean of a Gaussian.
From playlist Machine Learning
(ML 10.6) Predictive distribution for linear regression (part 3)
How to compute the (posterior) predictive distribution for a new point, under a Bayesian model for linear regression.
From playlist Machine Learning
(ML 10.7) Predictive distribution for linear regression (part 4)
How to compute the (posterior) predictive distribution for a new point, under a Bayesian model for linear regression.
From playlist Machine Learning
(ML 10.5) Predictive distribution for linear regression (part 2)
How to compute the (posterior) predictive distribution for a new point, under a Bayesian model for linear regression.
From playlist Machine Learning
33 - Normal prior conjugate to normal likelihood - intuition
This video provides some intuition for the properties of the posterior distribution for the case of a normal prior and likelihood. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdio
From playlist Bayesian statistics: a comprehensive course
(ML 10.4) Predictive distribution for linear regression (part 1)
How to compute the (posterior) predictive distribution for a new point, under a Bayesian model for linear regression.
From playlist Machine Learning
Stanford CS229: Machine Learning | Summer 2019 | Lecture 9 - Bayesian Methods - Parametric & Non
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3ptRUmB Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html
From playlist Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati)
Kerrie Mengersen: Bayesian Modelling
Abstract: This tutorial will be a beginner’s introduction to Bayesian statistical modelling and analysis. Simple models and computational tools will be described, followed by a discussion about implementing these approaches in practice. A range of case studies will be presented and possibl
From playlist Probability and Statistics
Aki Vehtari: Model assessment, selection and averaging
Abstract: The tutorial covers cross-validation, and projection predictive approaches for model assessment, selection and inference after model selection and Bayesian stacking for model averaging. The talk is accompanied with R notebooks using rstanarm, bayesplot, loo, and projpred packages
From playlist Probability and Statistics
Statistical Rethinking Fall 2017 - week02 lecture04
Week 02, lecture 04 for Statistical Rethinking: A Bayesian Course with Examples in R and Stan, taught at MPI-EVA in Fall 2017. This lecture covers Chapter 4. Slides are available here: https://speakerdeck.com/rmcelreath Additional information on textbook and R package here: http://xcel
From playlist Statistical Rethinking Fall 2017
JASP 0.14 Tutorial: Learn Bayes Module PART 1 (Binomial Estimation) (Episode 24)
In this JASP tutorial, I learn how to understand Bayesian statistical methods using the "Learn Bayes" module, available in the latest version of JASP! I did not do Bayesian stats in graduate school, and most frequently use classical/frequentist statistical methods. In "part one" of my two-
From playlist JASP Tutorials
Statistical Rethinking 2022 Lecture 02 - Bayesian Inference
Bayesian updating, sampling posterior distributions, computing posterior and prior predictive distributions Course materials: https://github.com/rmcelreath/stat_rethinking_2022 Intro music: https://www.youtube.com/watch?v=QH_VKWStK98 Chapters: 00:00 Introduction 04:53 Garden of forking
From playlist Statistical Rethinking 2022
Statistical Rethinking 2022 Lecture 07 - Overfitting
Slides and other course materials: https://github.com/rmcelreath/stat_rethinking_2022 Music: Intro: https://www.youtube.com/watch?v=R9bwnY05GoU Pause: https://www.youtube.com/watch?v=wAPCSnAhhC8 Chapters: 00:00 Introduction 04:26 Problems of prediction 07:00 Cross-validation 22:00 Regula
From playlist Statistical Rethinking 2022
Statistical Rethinking 2023 - 03 - Geocentric Models
Slides and other materials: https://github.com/rmcelreath/stat_rethinking_2023 Intro music: https://www.youtube.com/watch?v=ayARo_IGV7g Flow: https://www.youtube.com/watch?v=oriuG649ypM Pause: https://www.youtube.com/watch?v=lT5lFeaInl4 Outline 00:00 Introduction 13:56 Gaussian distribut
From playlist Statistical Rethinking 2023
From playlist COMP0168 (2020/21)
34 - Normal prior and likelihood - prior predictive distribution
This video provides a derivation of the normal prior predictive distribution for the case of a normal prior distribution and likelihood. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9
From playlist Bayesian statistics: a comprehensive course