๐๏ธ Week 07 - Lab on Bayesian classification with MCMC
In this week, we will have a lab session focused on Bayesian classification (logistic regression) with MCMC. Starting from a simple binary classification problem, we will implement a Bayesian logistic regression model and use the Metropolis-Hastings algorithm to sample from the posterior distribution of the model parameters. We will then explore how to make predictions using the posterior samples and how to evaluate the model performance. Finally, we will discuss practical considerations for implementing MCMC algorithms, including convergence diagnostics and the choice of proposal distributions.
๐งช Lab
Labs are available on GitHub. The lab for this week is Logistic regression with MCMC.
Check the README file for instructions on how to run the lab.
Google Colab is the suggested way to edit and execute the labs. Simply click on the icon to open the corresponding notebook in Colab.
We for the first lab, you can 