Bayesian Machine Learning

Bayesian Machine Learning Project

This is a collection of algorithms and models written in Python for probabilistic programming. The main focus of the package is on Bayesian reasoning by using Bayesian networks, Markov networks, and their mixing.

Numerical experiments to illustrate theoretical points of the article: A non-asymptotic analysis for stein variational gradient descent, Korba et al., 2021

The aim of this project is to apply Bayesian Machine Learning Algorithm to predict the diagnosis condition of the patients.

Repo of udemy bayesian machine learning A/B test

A Bayesian approach to predictive uncertainty in chemotherapy patients at risk of acute care utilization

Exercises on Bayesian linear regression, Gaussian Processes, Metropolis-Hastings Inference for Bayesian Logistic Regression, K-means and Probabilistic PCA. Made at Institut EURECOM (FR)

Assignment code for Bayesian ML course on Coursera

Platform for automatic processing of (aq-tngapms) Air Quality using TNGAPMS

Exploration of TensorFlow-2 and TensorFlow probability to implement Bayesian Neural Networks, Normalizing flows, real NVPs and Autoencoders. Exploration of Bayesian Modelling and Variational Inference with Pyro.

Library for Bayesian machine learning

Bayesian methods for machine learning course at CentraleSupélec

Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.

Key words: Bayesian analysis, Probabilistic programming, Data analysis, Bayesian machine learning... Using Python with its library PyMC3, pandas...

This is a GitHub repository for our Bayeisan Machine Learning textbook, which includes the PDF for the book and accompanying Python notebooks.

BayesianNonparametrics in julia

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.