cs401r_w2017
Winter 2017 - CS401r - Modern Data Analysis with Statistical ML
Resources
General notes on ipython and seaborn
You should become intimately familiar with numpy's broadcasting
Labs
Lab 2 - Bayesian concept learning
Lab 4 - Gaussian process regression
Lab 5 - Large-scale Gaussian process regression
Lab 6 - Expectation maximization
Lab 8 - Localization with particle filters
Lab 9 - LDA, General Conference, and Gibbs sampling
Lab 10 - Metropolis Hastings and Hamiltonian MCMC
Old labs we probably won't use
cs401r_w2017.txt · Last modified: 2021/06/30 23:42 (external edit)
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