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推荐理解Bayesian Method的好课程 - Radford Neal's CSC 2541
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CSC 2541 - Topics in Machine Learning: Bayesian Methods for
Machine Learning (Jan-Apr 2011) Week 1: Course info, Introduction, Conjugate priors
Week 2: Monte Carlo, Importance sampling, MCMC, Metropolis Algorithm
Week 3: Gibbs sampling, slice sampling, MCMC accuracy, multiple chains
Week 4: Bayesian mixture models, MCMC for mixtures, infinite mixtures.
Week 5: Linear basis function models, regularization.
Week 6: Inference using marginal likelihood, inference in terms of observed data, infinite basis function models.
Week 7: Gaussian process regression models.
Week 8: Gaussian process classification, hierarchical Bayesian models.
非常赞的一门课程，Lecture Notes写的非常好，Radfor Neal本身就是大家，其教授的课程自然也是出自自身研究所得。
https://blog.sciencenet.cn/blog-255110-420907.html
上一篇：Papers on LDA
下一篇：Python中改变当前工作目录
Week 2: Monte Carlo, Importance sampling, MCMC, Metropolis Algorithm
Week 3: Gibbs sampling, slice sampling, MCMC accuracy, multiple chains
Week 4: Bayesian mixture models, MCMC for mixtures, infinite mixtures.
Week 5: Linear basis function models, regularization.
Week 6: Inference using marginal likelihood, inference in terms of observed data, infinite basis function models.
Week 7: Gaussian process regression models.
Week 8: Gaussian process classification, hierarchical Bayesian models.
非常赞的一门课程，Lecture Notes写的非常好，Radfor Neal本身就是大家，其教授的课程自然也是出自自身研究所得。
https://blog.sciencenet.cn/blog-255110-420907.html
上一篇：Papers on LDA
下一篇：Python中改变当前工作目录
