M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.
A collection of Methods and Models for various architectures of Artificial Neural Networks
Project of IEEE/ACM TASLP “Bayesian Neural Network Language Modeling for Speech Recognition”
Comparison of Several Bayesian Regression Techniques and Gaussian Processes
This is the code for post-processing the shallow shadow tomography data and doing error mitigation on the noisy hardware.
Repository that contains the projects of the Probabilistic Artificial Intelligence class offered in Fall 2021 at ETH Zurich
Walmart sales prediction with Linear Regression and Random Forests + Bayesian Structure Learning
Application of OPAL (Occam Plausibility Algorithm) based Bayesian learning to SEIRD model of COVID-19 disease spread in Texas
Exercises for the "Data Analytics" course, University of Bologna (2021/2022)
Colorectal cancer risk mapping through Bayesian Networks
Learning parameters for a bayesian network based on health records data -Assignment 4 (Artificial Intelligence: COL333)
computational modelling for restless bandit behavioural data (thalamotomy oedema work)
A fork of a Bayesian learning and inference for state space models library, created due to some dependencies mismatching and for posterity because it's used in a private Colab notebook.
Control architecture for an agent that perceives, plans, learns, and acts in a 3D MMORPG. Evolved from a monolith through reactive rules, state machines, and utility scoring to GOAP planning. JPS/A* pathfinding, DDA line-of-sight, Bayesian adaptation. Pure Python 3.14 (free-threaded), zero dependencies.
Implementation of FOD-learn (fully observed data), Expectation Maximisation(Partially Observed Data) and Latent Variable Learning in Bayesian Network
My PDF solutions to our courseworks for the 2024-2025 year
My Programming Assignments from the CPE 695 Applied Machine Learning Course from Stevens Institute of Technology
Making use of bayesian learning, three common applications are developed.
Visualizing Bayesian Learning
Final project for Bayesian learning & Montecarlo simulation course attended at Polimi in 2022. The objective is to build a Bayesian model able to predict the quality of a given wine
Add a description, image, and links to the bayesian-learning topic page so that developers can more easily learn about it.
To associate your repository with the bayesian-learning topic, visit your repo's landing page and select "manage topics."