2014 April

• Some status updates

  There are a lot of things I want to post to both here and my personal blogs. However I was sucked into sanctuary for the most of last month. I guess after a month of playing, it is probably time to slowly resume my personal projects.

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Random Posts

• Random notes on Pandas and Scikit-learn

  So I first heard about Panda probably a year ago when I was in my previous job. It looked nice, but I didn’t really get the chance to use it. So practically it is a library that makes data looks like a mix of relational database table and excel sheet. It is easy to do query with it, and provides a way to process it fast if you know how to do it properly (no, I don’t, so I cheated).

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• MVC : Me vs. CodeIgniter

  Background

  While my static pages and site theme is still under construction, I went to CodeIgniter.com to see how to work with it and played the tutorial screencasts. The reason behind in considering CodeIgniter (CI) to be used in my next project is because I don’t feel like re-inventing the wheel. However to port my current project to use CI may cause some problems as there are differences in how we implement MVC structure.

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• Seriously, What can I do with Semantic Web?

  Semantic Web always sounds like some magic power stuff that a group of people keep yelling about. Chances are, if one is into web development, he/she would have heard of it somehow or other. However, despite the supposedly wide awareness about it, are we using it? Or rather, am I publishing enough data to Semantic Web? OK, I don’t, but why?

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• Performing Statistical Analysis with Python

  This is the year I kept digging my old undergraduate notes on Statistics for work. First was my brief attempt wearing the Data Scientist performing ANOVA test to see if there’s correlation between pairs of variables. Then just recently I was tasked to analyze a survey result for a social audit project.

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• Fuzzy C-Means and Content Recommendation

  This post is purely based on my own speculation as there’s no experiment on real-life data to actually back the arguments. I am currently trying to document down a plan for my experiment(s) on recommender system (this reminds me that I have not release the Flickr data collection tool :/) and my supervisor advised to write a paragraph or two on some of the key things. Since he is not going to read it, so I might as well just post it here as a note.

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