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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 - install anaconda]] | ||
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- | [[cs401r_w2016:lab2|Lab 2 - sampling and likelihood]] | ||
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- | [[cs401r_w2016:lab3|Lab 3 - basic PDF library]] | ||
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- | [[cs401r_w2016:lab4|Lab 4 - Gaussian process regression]] | ||
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- | [[cs401r_w2016:lab5|Lab 5 - MNIST with KDE]] | ||
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- | [[cs401r_w2016:lab6|Lab 6 - Bayesian Concept Learning]] | ||
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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, wikipedia, and Gibbs sampling]] | ||
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- | [[cs401r_w2016:lab10|Lab 10 - improved generative images with MCMC]] | ||
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- | [[cs401r_w2016:lab11|Lab 11 - Bayesian super resolution]] | ||
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- | [[cs401r_w2016:lab12|Lab 12 - weather data with BP]] | ||
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- | [[cs401r_w2016:lab13|Lab 13 - recommender system]] | ||