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Pete Skomoroch

datawrangling.com · Personal blog · on HN since 2007

Pete Skomoroch is a data scientist who writes about datasets, machine learning, and large-scale data processing with tools like Hadoop and AWS.

What HN saysCommenters share his lists of public datasets and free video courses in math, science, and engineering, plus a post on FlightCaster's flight predictions.
20HN people shared it
14linked it in comments
12stories submitted
242story points
12 years agolast shared
2007people per year2026

Most-shared posts

  1. 1
    Some Datasets Available on the Web
    8 people · 47 points · first shared 2008 · 6 comments on HN
  2. 2
    How FlightCaster Squeezes Predictions from Flight Data
    4 people · 93 points · first shared 2009 · 16 comments on HN
  3. 3
  4. 4
    List of Datasets on the Web
    2 people · 31 points · first shared 2008 · 4 comments on HN
  5. 5
    Hidden Video Courses in Math, Science, and Engineering
    1 people · 37 points · first shared 2008 · 6 comments on HN
  6. 6
    Python Montage Code for Displaying Arrays
    1 people · 14 points · first shared 2008 · discussion on HN
  7. 7
    Amazon Web Services Public Datasets
    1 people · 6 points · first shared 2008 · 1 comments on HN
  8. 8
    Amazon Elastic MapReduce: A Web Service API for Hadoop
    1 people · 5 points · first shared 2009 · 1 comments on HN
  9. 9
    MPI Cluster with Python and Amazon EC2
    1 people · 4 points · first shared 2008 · discussion on HN
  10. 10
    Wikipedia Page Traffic Statistics Dataset
    1 people · 3 points · first shared 2009 · discussion on HN
  11. 11
    On-Demand MPI Cluster with Python and EC2
    1 people · 2 points · first shared 2008 · discussion on HN
  12. 12
  13. 13
    Python montage code for displaying arrays
    1 people · first shared 2008
  14. 14
    Homepage
    1 people · first shared 2010

What HN people wrote when they linked it

grrrr · 2010-05-04
The book by Manning (freely available online) has already been recommended. I would start with this. In addition there are a wealth of online video lectures that may inspire you: http://www.datawrangling.com/hidden-video-courses-in-math-science-and-… and http://videolectures.net/mlss04_hofmann_irtm/ and http://videolectures.net/Top/Computer_Science/ In so far as search engines go it's certainly worth playing around with Lucene. It's well implemented and you'll learn a lot of what really matters when it comes to indexing and retrieval. For the text processing (classification, data extraction) side It may also be worth brushing up on your stats (a good excuse to learn R) and checking out Mahout http://lucene.apache.org/mahout/
keefe · 2009-06-19
I think there are some interesting lectures here http://www.datawrangling.com/hidden-video-courses-in-math-science-and-… and I occasionally find something insightful here http://demonstrations.wolfram.com/ but I'm in a similar position as you, unfortunately...
dood · 2007-08-12
It depends on the context you are using it in! For social news (e.g. reddit et al.), this sort of thing might be a great help at providing personal recommendations. Here is a fun recent paper from google, about 'Scalable Online Collaborative Filtering' for their personalised news service [http://www2007.org/paper570.php], using MapReduce to run Expectation Maximization. via [http://www.datawrangling.com/google-paper-on-parallel-em-algorithm-usi…
diegogomes · 2011-10-17
Another cool related list can be found here: http://www.datawrangling.com/some-datasets-available-on-the-web
jimbokun · 2010-11-08
Otherwise known as "wrap the crap." http://www.datawrangling.com/how-flightcaster-squeezes-predictions-fro… "Building layer upon layer of abstraction is a big key. On the jvm, you have to do this, it is the path around the verbosity of Java and the vast abyss of poorly done APIs. You just keep searching until you finally find the folks who have built a sane, high level API on top of the thing you want to use - then you wrap it in a high level language like Clojure. The technical term for this is 'wrap the crap.'"
physcab · 2009-08-15
uc irvine machine learning repository. http://archive.ics.uci.edu/ml/ it's where the netflix dataset is headed. you'll find many datasets there that have been used in scientific papers as well, so you can benchmark whatever tests you want to run. the data wrangling blog also has a pretty good list of datasets: http://www.datawrangling.com/some-datasets-available-on-the-web
pskomoroch · 2008-11-13
Numpy/Scipy syntax is very close to matlab, but python is a lot more powerful. I port matlab code over to python pretty frequently. A toy example is here along links to other comparisons: http://www.datawrangling.com/python-montage-code-for-displaying-arrays

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