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Chicago Machine Learning Meetup

  • May 9, 2012 · 5:30 PM
  • This location is shown only to members

May's meetup will be in the "interactive study group" style.  For this meetup, Xiao Dong will be leading the discussion on unsupervised learning and comparing these to supervised and semi-supervised techniques.  Unsupervised learning refers to a collection of techniques that attempt to find structure in (unlabeled) data.  These are generally exploratory techniques of which clustering is a prime example.




Andrew Ng Machine Learning Lecture 12 (First 18 minutes)

K Means Clustering Lecture Notes by Andrew Ng

Craig Struble's Clustering Presentation

KNN classification:

A brief introduction to KNN


Xiao Dong, PhD is a research scientist at University of Illinois Medical Center. Xiao's research experience related to Machine Learning includes applying supervised and unsupervised algorithms in Bioinformatics and Social Media analyses. Xiao is also a very active member in Ruby on Rails, Node.js and iOS communities.




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  • Ben S.

    I was a bit disappointed. Kmeans is such a simple algorithm to understand if you just think about it visually. Even in graduate school I never understood using mathematical notation when pseudo or even real code would have made more sense for this example. I found dozens of examples with a simple google search. I think the fact that k-means converges is possibly its least interesting quality, but that is just my opinion. I would put it with bubble sort as one of those algorithms that everybody has to learn, but nobody uses.

    May 10, 2012

  • Ameena L.

    Only regret is that I have to leave early due to other commitment. Otherwise discussion was going on great and participation and input from various people were precious gems of knowledge. Topic was very relevant to this meetup.

    May 10, 2012

  • Gregory P.

    Awesome presentation on k-means.

    May 10, 2012

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