Posts in intermediate
GLM: Model Selection
- 08 January 2022
- Category: intermediate
A fairly minimal reproducable example of Model Selection using WAIC, and LOO as currently implemented in PyMC3.
GLM: Robust Regression using Custom Likelihood for Outlier Classification
- 17 November 2021
- Category: intermediate
Using PyMC3 for Robust Regression with Outlier Detection using the Hogg 2010 Signal vs Noise method.
Hierarchical Binomial Model: Rat Tumor Example
- 11 November 2021
- Category: intermediate
This short tutorial demonstrates how to use PyMC3 to do inference for the rat tumour example found in chapter 5 of Bayesian Data Analysis 3rd Edition [Gelman et al., 2013]. Readers should already be familliar with the PyMC3 API.
A Primer on Bayesian Methods for Multilevel Modeling
- 09 November 2021
- Category: intermediate
Hierarchical or multilevel modeling is a generalization of regression modeling. Multilevel models are regression models in which the constituent model parameters are given probability models. This implies that model parameters are allowed to vary by group. Observational units are often naturally clustered. Clustering induces dependence between observations, despite random sampling of clusters and random sampling within clusters.
Estimating parameters of a distribution from awkwardly binned data
- 23 October 2021
- Category: intermediate
Let us say that we are interested in inferring the properties of a population. This could be anything from the distribution of age, or income, or body mass index, or a whole range of different possible measures. In completing this task, we might often come across the situation where we have multiple datasets, each of which can inform our beliefs about the overall population.
Variational Inference: Bayesian Neural Networks
- 20 October 2021
- Category: intermediate
There are currently three big trends in machine learning: Probabilistic Programming, Deep Learning and “Big Data”. Inside of PP, a lot of innovation is in making things scale using Variational Inference. In this blog post, I will show how to use Variational Inference in PyMC3 to fit a simple Bayesian Neural Network. I will also discuss how bridging Probabilistic Programming and Deep Learning can open up very interesting avenues to explore in future research.
Hierarchical Partial Pooling
- 07 October 2021
- Category: intermediate
Suppose you are tasked with estimating baseball batting skills for several players. One such performance metric is batting average. Since players play a different number of games and bat in different positions in the order, each player has a different number of at-bats. However, you want to estimate the skill of all players, including those with a relatively small number of batting opportunities.
GLM: Mini-batch ADVI on hierarchical regression model
- 23 September 2021
- Category: intermediate
Unlike Gaussian mixture models, (hierarchical) regression models have independent variables. These variables affect the likelihood function, but are not random variables. When using mini-batch, we should take care of that.
Probabilistic Matrix Factorization for Making Personalized Recommendations
- 20 September 2021
- Category: intermediate
So you are browsing for something to watch on Netflix and just not liking the suggestions. You just know you can do better. All you need to do is collect some ratings data from yourself and friends and build a recommendation algorithm. This notebook will guide you in doing just that!
Marginalized Gaussian Mixture Model
- 18 September 2021
- Category: intermediate
Gaussian mixtures are a flexible class of models for data that exhibits subpopulation heterogeneity. A toy example of such a data set is shown below.
Gaussian Mixture Model
- 18 September 2021
- Category: intermediate
Original NB by Abe Flaxman, modified by Thomas Wiecki
Rolling Regression
- 15 September 2021
- Category: intermediate
Pairs trading is a famous technique in algorithmic trading that plays two stocks against each other.
A Hierarchical model for Rugby prediction
- 30 August 2021
- Category: intermediate
Based on the following blog post: Daniel Weitzenfeld’s, which based on the work of Baio and Blangiardo.