Notebooks about Bayesian methods for machine learning

Python package for Bayesian Machine Learning with scikit-learn API

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

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

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

BayesianNonparametrics in julia

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

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

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.

Bayesian methods for machine learning course at CentraleSupélec

Efficient approximate Bayesian machine learning

Library for Bayesian machine learning

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

Repo of udemy bayesian machine learning A/B test

Bayesian Machine Learning

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

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