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Reading other people’s blogs

It’s really nice to find blogs of people who are passionate in data.  Most of them have so much experience as developers or database engineers and are determined to move forth with their ideal job of becoming a data scientist.

Latest blog I found is from http://devnambi.com/, a link that came up on my Google alerts for all things related to “data scientist”.  Learnt that there is a Data Science certificate program from the University of Washington.  Oh how I would love to go for the 9 month course in Seattle.  It’s not too costly, but no student visa makes is a huge obstacle. Not to mention that my last semester would have also began by then.

So for the last semester the modules I might read are:

  1. Multivariate data analysis
  2. Statistical methods: Theory/Applications
  3. High dimensionality data analysis
  4. Knowledge discovery and data mining

Unfortunately 1 and 4 clashes.  So have to pick either 1 or 4 and the remaining 2 and 3.  Can’t wait for classes to start.

Recently been looking at Kaggle again, after the hiatus due to holiday and D3-ing.  In the meantime, I’m just wishing for the heat to go away and more luck!

 

 

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Finding problems to solve

Part of me can’t wait for school to start, at least then I have to pick up new skills from Professors and school. I have trouble finding an environment where I can immerse myself in data analysis – whether big data or not it doesn’t matter. I’m looking at baby steps. Kaggle is a great place to start, but that will come after work and on weekends. I wish i can do that on a daily basis. Look at data, play with it, discover new things from it.

Cross my fingers for a data scientist internship and leave my slide monkey past behind.

New link rdatamining.com

Once I get back to work from my holiday, I’ll look at the good links aggregated by rdatamining.com

http://www.rdatamining.com/resources/onlinedocs

 

 

Tidying Data

Wish I had read this earlier.

http://vita.had.co.nz/papers/tidy-data-pres.pdf

http://files.meetup.com/1677477/R_Group_June_2011.pdf

 

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mathbabe

Exploring and venting about quantitative issues

The Stone and the Shell

Using large digital libraries to advance literary history

Hi. I'm Hilary Mason.

Zoom out, zoom in, zoom out.

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Blog to document and reflect on Columbia Data Science Class

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[R] + applied economics.

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Scientific computing, data viz and general geekery, with examples in R and MATLAB.