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cs401r_w2018 [2018/01/08 13:19] (current)
wingated created
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 +==== Winter 2018 - CS401r - Modern Data Analysis with Statistical ML ====
 +
 +----
 +=== Resources ===
 +
 +[[cs401r_w2016:​lab_notes|General notes on ipython and seaborn]]
 +
 +You should become intimately familiar with [[http://​docs.scipy.org/​doc/​numpy-1.10.1/​user/​basics.broadcasting.html|numpy'​s broadcasting]]
 +
 +----
 +=== Labs ===
 +
 +[[cs401r_w2016:​lab1|Lab 1 - Anaconda and pandas]]
 +
 +[[cs401r_w2016:​lab2|Lab 2 - Bayesian concept learning]]
 +
 +[[cs401r_w2016:​lab5|Lab 3 - MNIST with KDE]]
 +
 +[[cs401r_w2016:​lab4|Lab 4 - Gaussian process regression]]
 +
 +[[cs401r_w2016:​lab14|Lab 5 - Large-scale Gaussian process regression]]
 +
 +[[cs401r_w2016:​lab13|Lab 6 - Expectation maximization]]
 +
 +[[cs401r_w2016:​lab7|Lab 7 - Kalman filter]]
 +
 +[[cs401r_w2016:​lab8|Lab 8 - Localization with particle filters]]
 +
 +[[cs401r_w2016:​lab9|Lab 9 - LDA, General Conference, and Gibbs sampling]]
 +
 +[[cs401r_w2016:​lab10|Lab 10 - Metropolis Hastings and Hamiltonian MCMC]]
 +
 +[[cs401r_w2016:​lab12|Lab 11 - Recommender system]]
 +
 +[[cs401r_w2016:​fp|Final project]]
 +
 +----------------
 +
 +Old labs we probably won't use
 +
 +[[cs401r_w2016:​lab3|Lab 3 - basic PDF library]]
 +
 +[[cs401r_w2016:​lab11|Lab 11 - Bayesian super resolution]]
 +
  
cs401r_w2018.txt ยท Last modified: 2018/01/08 13:19 by wingated