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cs401r_w2016 [2016/03/17 22:33]
admin
cs401r_w2016 [2021/06/30 23:42]
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-==== Winter 2016 - CS401r - Modern Data Analysis with Statistical ML ==== 
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-=== Labs === 
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-[[cs401r_w2016:​lab_notes|General notes on ipython and seaborn]] 
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-[[cs401r_w2016:​lab1|Lab 1 - Anaconda and pandas]] 
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-[[cs401r_w2016:​lab2|Lab 2 - Bayesian concept learning]] 
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-[[cs401r_w2016:​lab5|Lab 3 - MNIST with KDE]] 
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-[[cs401r_w2016:​lab4|Lab 4 - Gaussian process regression]] 
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-[[cs401r_w2016:​lab14|Lab 5 - Large-scale Gaussian process regression]] 
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-[[cs401r_w2016:​lab13|Lab 6 - Expectation maximization]] 
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-[[cs401r_w2016:​lab7|Lab 7 - Kalman filter]] 
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-[[cs401r_w2016:​lab8|Lab 8 - Localization with particle filters]] 
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-[[cs401r_w2016:​lab9|Lab 9 - LDA, General Conference, and Gibbs sampling]] 
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-[[cs401r_w2016:​lab10|Lab 10 - Metropolis Hastings and Hamiltonian MCMC]] 
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-[[cs401r_w2016:​lab12|Lab 11 - Recommender system]] 
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----------------- 
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-Old labs we probably won't use 
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-[[cs401r_w2016:​lab3|Lab 3 - basic PDF library]] 
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-[[cs401r_w2016:​lab11|Lab 11 - Bayesian super resolution]] 
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cs401r_w2016.txt ยท Last modified: 2021/06/30 23:42 (external edit)