Notebooks about Bayesian methods for machine learning

Python package for Bayesian Machine Learning with scikit-learn API

A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Code for "A-NICE-MC: Adversarial Training for MCMC"

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

BayesianNonparametrics in julia

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

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

Efficient approximate 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.

Library for Bayesian machine learning

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.

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

Notebook from masters course in Probabilistic Cognitive Modelling @ University of Helsinki. Includes manual calculation of response distribution and Bayesian observer likelihoods.

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

This is about Bishops Machine Learning tools implementation in a structured way with strong OOP practices, Video implementations in Tunisian dialect

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