Notes on codes, projects and everything
I have been following this excellent guide written by Benjamin Thomas to set up my virtual machine for development purpose. However, when I am starting to configure a Ubuntu Quantal alpha machine, parts of the guide became inapplicable. Hence, this post is written as a small revision to the previously mentioned guide.
While following through the Statistical Learning course, I came across this part on doing regression with boosting. Then reading through the material, and going through it makes me wonder, the same method may be adapted to Erik Bernhardsson‘s annoy algorithm.
(more…)Writing a usable form and database library has always been a painful experience. So why bother re-inventing the wheel when there are so many to choose from already? I am writing one mostly for learning purpose. After numerous attempts, I finally get my form and database library in shape. It is nowhere complete, but nor it is perfect, but it is currently the implementation that is closest to my original design. I will keep working on it so it can be used in my personal projects in the future.
After a miserable trip back to academic world, I finally re-gained the courage to get back to job-market. For the time spent in university, I spent quite some time reading about Semantic Web and RDF. Then I thought, I should have published more in this format in future. However, that didn’t really happen, mostly because I am too lazy.
After coded enough Javascript few months back, I found that there are a couple of functions that I kept re-using in different projects. Therefore I took some time to refactor them and re-arrange them into a single file. The common code that I keep reusing even today consists of functions that does prototypical inheritance, scope maintenance, some jquery stuff, google maps api stuff and some general ajax application related code.
I came across a video on Youtube on Pi day. Coincidently it was about estimating the value of Pi produced by Matt Parker aka standupmaths. While I am not quite interested in knowing the best way to estimate Pi, I am quite interested in the algorithm he showed in the video however. Specifically, I am interested to find out how easy it is to implement in Python.