Created
August 17, 2016 21:03
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Finally posting my 389-page tutorial | |
"data science @ the new york times" | |
from last week's Machine Learning Summer School | |
in Arequipa, Peru ( http://mlss.cc/ ) | |
here: http://www.slideshare.net/chrishwiggins/machine-learning-summer-school-2016 | |
Topics include: | |
descriptive/predictive/prescriptive modeling | |
(unsupervised/supervised/reinforcement learning), | |
pp75-95 | |
boosting & surrogate loss functions pp103-117 | |
causality via generative models (p141-215) | |
POISE: “policy optimization via importance sample estimation” pp 147-187 | |
connection w/causal inference & matching (p188-215) | |
brief intro to instrumental variables (p230-248) | |
bandits (p249-316) | |
connecting thompson sampling with generative modeling (p259-305) |
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