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schedule [2016/11/15 13:46] asa |
schedule [2016/11/16 10:13] asa |
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| Tuesday | Nearest neighbor methods ({{wiki:15_nearest_neighbors.pdf | slides}}); [[code:nearest_neighbors | demo]]. | Chapter e-6 | | | | Tuesday | Nearest neighbor methods ({{wiki:15_nearest_neighbors.pdf | slides}}); [[code:nearest_neighbors | demo]]. | Chapter e-6 | | | ||
| Thursday | Clustering ({{wiki:16_clustering.pdf | slides}}) kmeans [[http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html | demo]] | Chapter 10 in [[http://www-bcf.usc.edu/~gareth/ISL/ | introduction to statistical learning]] | | | | Thursday | Clustering ({{wiki:16_clustering.pdf | slides}}) kmeans [[http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html | demo]] | Chapter 10 in [[http://www-bcf.usc.edu/~gareth/ISL/ | introduction to statistical learning]] | | | ||
- | ^ Week 12: November 15,17 | | | | | + | ^ Week 13: November 15,17 | | | | |
| Tuesday | Naive Bayes classification ({{wiki:18_naive_bayes.pdf | slides}}); [[code:naive_bayes | demo]]. | | | | | Tuesday | Naive Bayes classification ({{wiki:18_naive_bayes.pdf | slides}}); [[code:naive_bayes | demo]]. | | | | ||
- | | Thursday | | TBD | | | + | | Thursday | Intro to computational learning theory ({{wiki:19_vc_dimension.pdf | slides}}) | Chapter 1.3 in the textbook | | |
- | + | ^ Thanksgiving break | | | | | |
- | ... | + | ^ Week 14: November 29, December 1 | | | | |
- | |< 100% 18% 40% 19% 13% >| | + | | Tuesday | The VC dimension ({{wiki:20_vc_dimension.pdf | slides}}). | Chapter 2.1, 2.2 in the textbook | | |
+ | | Thursday | Ensemble models | | | | ||
^ Week 15: December 6,8 | | | | | ^ Week 15: December 6,8 | | | | | ||
| Tuesday | Course summary | | | | | Tuesday | Course summary | | | | ||
| Thursday | Poster session | | | | | Thursday | Poster session | | | | ||
- | | + | ^ Week 16 | | | | |
+ | | Tuesday | Submit final reports | | | | ||
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