Implementing MCMC sampling from scratch in R for various Bayesian models
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Updated
Dec 7, 2023 - HTML
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.
My implementation of homework 2 for the Machine Learning class in NCTU (course number 5088).
Machine Learning Projects on Linear Regression, Classification and Multi-layer Perceptrons, and Gaussian Processes and SVMs (October, 2019).
Comparing frequentist linear regression with bayesian linear regression of a lying experiment
Comparison of different regression and classification algorithms on different datasets.
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