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Toby Segaran
blog.kiwitobes.com · Personal blog · on HN since 2008
Toby Segaran, author of Programming Collective Intelligence, blogs about data analysis, Python examples and his books.
What HN saysHN commenters point to it for Python examples and source code from his book, and for his bullet-point notes on a data book.
15HN people shared it
5linked it in comments
12stories submitted
123story points
14 years agolast shared
2008people per year2026
Most-shared posts
- 1Walmart Growth Video3 people · 4 points · first shared 2008 · discussion on HN
- 2Personal data integration (part 1)2 people · 6 points · first shared 2008 · discussion on HN
- 3"Why Semantics?" - an excellent intro to semantic data2 people · 3 points · first shared 2009 · discussion on HN
- 4Notes on “Predictably Irrational” by Dan Ariely2 people · 3 points · first shared 2008 · 1 comments on HN
- 5Homepage2 people · first shared 2008
- 6Programming Collective Intelligence author has 2 new books out1 people · 42 points · first shared 2009 · 3 comments on HN
- 7A network graph of Corporate America1 people · 41 points · first shared 2008 · 15 comments on HN
- 8Lessons on recommendation systems1 people · 12 points · first shared 2008 · discussion on HN
- 9The "excluded middle" of technical books1 people · 8 points · first shared 2008 · 2 comments on HN
- 10A San Francisco restaurant health-map (with code)1 people · 2 points · first shared 2008 · discussion on HN
- 11Toby Seagaran on Freerisk1 people · 2 points · first shared 2009 · discussion on HN
- 12Post 441 people · first shared 2009
- 13Post 421 people · first shared 2010
What HN people wrote when they linked it
arscan · 2012-10-24
Very cool. Personally I find animated maps to be the easiest way to digest this kind of data (like the animation of nuclear testing[1] or walmart proliferation[2]). Looks like it would only take a few lines of javascript to accomplish this kind of "flipbook" animation. Just a thought -- great job regardless.
[1] http://www.ctbto.org/specials/1945-1998-by-isao-hashimoto/
[2] http://blog.kiwitobes.com/?p=51
conesus · 2009-09-19
Yes, I can certainly point you in the right direction.
Toby Segaran, author of the highly esteemed and good-read Programming Collective Intelligence (published by O'Reilly, so you know it's good), released all of the source code that he talked about in the book. You can find it all here on his blog: http://blog.kiwitobes.com/?p=44.
He talks about hill climbing and variants (random restart, simulated annealing). He does a great job of explaining the algorithm and the math behind the hill climbing decisions. For optimization, something hill climbing is not even the best tool. Look at some of the other optimization strategies he employs (specifically the genetic mutation algorithm).
I highly recommend buying the book, even if only one chapter currently interests you. I bet you the other chapters will too. It's on Amazon, and at B&N if you want it this second.
reader5000 · 2010-09-08
Those results are highly odd, but I don't think okcupid is mainstream enough to really glean any insight into racial psychology (if such a thing exists) from their data. Furthermore, they don't provide enough info on their analysis method, but I would be interested in seeing the results of a null-run: randomly assigning profiles to groups (rather than by race) and seeing what "statistically distinct" phrases arise (if the analysis is valid no phrases should arise).
It would also be interesting to see them do the same analysis for other features such as height, income, photo attractiveness, etc.
Similar analysis for craigslist personals by city: http://blog.kiwitobes.com/?p=42
kakooljay · 2009-10-06
There's tons of Python examples on Toby Segaran's blog:
http://blog.kiwitobes.com
I know you've read some Python books, but you might want to check out Segaran's books too. The examples in Programming Collective Intelligence [http://oreilly.com/catalog/9780596529321] are all Python too I think..
toby · 2008-12-30
I shared my unedited notes on this book a few months ago. I felt the book had a few really cool findings and a lot of fluff, so I redid it as bullet-points:
http://blog.kiwitobes.com/?p=49