Implementing MCMC sampling from scratch in R for various Bayesian models

Markov Chain Monte Carlo (MCMC) and importance sampling in the context of Bayesian linear regression

2022 NTHU EE6550 (EE655000) Machine Learning Course Projects (include Maximum A Posteriori Estimation, Linear Regression, Neural Network Image Classification)

Bigmart Sales Analysis prediction of the sales, data set from https://datahack.analyticsvidhya.com/contest/practice-problem-big-mart-sales-iii/

Summer Research Internship Tasks

Bayesian Linear regression using MCMC and Variational Inference

Coresets for scalable robust pseudo-Bayesian inference

Sklearn wrapper for Bayesian Probabilistic Matrix Completion with Macau, Smurff, and Bayesian linear regression

Repo for course CSC2558: "Intelligent Adaptive Interventions" project in nonstationary contextual bandits.

Ensembled Deep Network for Global Optimization

Bayesian linear and Gaussian process regression to predict CO2 concentration as a function of time

Entraînement de modèles Bayésiens et analyse de robustesse.

code for performing Bayesian ARD regression, where covariates have groups

Model Comparison of 2-Component Mixture, 3-Component Mixture, and Bayesian Linear Regression with MCMC Sampling

My personal repository for Statistical Thinking course assignments, 8th semester, Computer Science Engineering.

Machine Learning Projects on Linear Regression, Classification and Multi-layer Perceptrons, and Gaussian Processes and SVMs (October, 2019).

My implementation of homework 2 for the Machine Learning class in NCTU (course number 5088).

Comparing frequentist linear regression with bayesian linear regression of a lying experiment

Comparison of different regression and classification algorithms on different datasets.