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

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

A fully Bayesian linear regression pipeline for predicting salaries with conjugate priors, Gibbs sampling, and model diagnostics.

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

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

Coresets for scalable robust pseudo-Bayesian inference

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

Ensembled Deep Network for Global Optimization

Entraînement de modèles Bayésiens et analyse de robustesse.

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

This project explores data analysis, blending core Probability Theory and Descriptive Statistics with Statistical Inference and Bayesian Machine Learning (Regression/Classification). It concludes with a comparative study of Frequentist vs. Bayesian A/B Testing.

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

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

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

Mini-course for Elizabeth Liu

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