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

Application of OPAL (Occam Plausibility Algorithm) based Bayesian learning to SEIRD model of COVID-19 disease spread in Texas

Walmart sales prediction with Linear Regression and Random Forests + Bayesian Structure Learning

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)

Implementation of FOD-learn (fully observed data), Expectation Maximisation(Partially Observed Data) and Latent Variable Learning in Bayesian Network

Making use of bayesian learning, three common applications are developed.

My Programming Assignments from the CPE 695 Applied Machine Learning Course from Stevens Institute of Technology

This repository contains golang code of Bayesian Learning on a diabetes dataset

Visualizing Bayesian Learning

Final project of the Data Visualization course, Ariel university.

My PDF solutions to our courseworks for the 2024-2025 year

Simple implementation of knn & Bayesian Learning & Random Forest from Scratch

Python implementation of Naive Bayes Classifier.