chrishwiggins

- tukey's 1962 paper on the tension between
mathematical statistics and applied computational statistics
http://web.stanford.edu/~gavish/documents/Tukey_the_future_of_data_analysis.pdf

- william cleveland's 2001 "data science" paper
http://www.datascienceassn.org/sites/default/files/Data%20Science%20An%20Action%20Plan%20for%20Expanding%20the%20Technical%20Areas%20of%20the%20Field%20of%20Statistics.pdf

- interview w/leo breiman, heretical statistician
http://projecteuclid.org/euclid.ss/1009213290

chrishwiggins

Q: I want to sign up for 3900 (supervised research). How many 
credits will you give me?

A: If you want to take 3900 with me, we need to come to a 
contract, and this contract needs to be closed before the start 
of the semester. The contract will stipulate: 


- Who is the scientific advisor (if not me)
- What is the deliverable (e.g., technical report, oral report)

chrishwiggins

Q: what book should i use to learn ML?

A: use several, and find the one that speaks to you.

the list below assumes you know a bit of math but
are not very mathematical, and are interested in learning
enough to be practical. that is, it is not at the
mathematical level of MIJ's alleged list
(cf. https://news.ycombinator.com/item?id=1055389 )

chrishwiggins

For current information please 
- see http://modelingsocialdata.org/ and 
- follow @CUSocialData ( https://twitter.com/CUSocialData )

official bulletin URL:
http://www.columbia.edu/cu/bulletin/uwb/subj/APMA/E4990-20151-001/

chrishwiggins

FAQ:

where are some fun datasets to play with?

1. CMU:
http://lib.stat.cmu.edu/datasets/

2. UCI:

a) MLR@UCI (machine learning repository / machine learning archive )

chrishwiggins

Q: what are "single tree-based" (as opposed to forest-based) supervised learning methods?

A: some of my favorites:

- ADT
    + wiki: http://en.wikipedia.org/wiki/Alternating_decision_tree
    + ref: http://perun.pmf.uns.ac.rs/radovanovic/dmsem/cd/install/Weka/doc/classifiers-papers/trees/ADTree/atrees.pdf

- rpart in R
    + http://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf

chrishwiggins

nice NPR story illustrating a conceptual and methodological 
difference between AI and ML, using some of the more 
press-grabbing, (human) game-beating systems:

http://www.npr.org/blogs/alltechconsidered/2015/01/08/375736513/look-out-this-poker-playing-computer-is-unbeatable

this story's pretty interesting in general but one particular 
part grabs my attention:

Oren Etzioni, the head of Seattle's Allen Institute for 

chrishwiggins

Links from talk "Engagement and Reality":

• TimesMachine: Thursday September 18, 1851 - NYTimes.com
• The New York Times Introduces a Web Site - NYTimes.com
• The New York Times Company | The New York Times Company
• The leaked New York Times innovation report is one of the key documents of this media age » Nieman Journalism Lab
• How The New York Times Works
• [Machine Learning For Journalism at The New York Times | Techjaw](http://techjaw.com/2015/02/01/machine-learning-for-journalism-at-the-new-york-times/?utm_conte

chrishwiggins

---------- Forwarded message ----------
From: chris wiggins <chris.wiggins@[YYY].edu>
Date: Wed, Aug 1, 2012 at 7:26 PM
Subject: stats history
To: hadley@[XXX].edu
Cc: chris wiggins <chris.wiggins@[YYY].edu>


Dear Hadley:

chrishwiggins

Links from talk "what is Data Science?" (hackNY lecture 2016-06-15):

context

• google search trends: data science

• indeed job trends: data science

• drew's data science venn diagram, sept 2010