Notes on codes, projects and everything
Implementing a Information Retrieval system is a fun thing to do. However, doing it efficiently is not (at least to me). So my first few attempts didn’t really end well (mostly uses just Go/golang with some bash tricks here and there, with or without a database). Then I jumped back to Python, which I am more familiar with and was very surprised with all the options available. So I started with Pandas and Scikit-learn combo.
Recently I volunteered in building a site that reports whether certain websites are blocked locally (please don’t ask why that is happening). As it is a very simple app reporting status I wanted it to be easily scrape-able. One of the decision made was I want it to have things to see on first load, this practically removes the possibility of using react, which is my current favorite.
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…)
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.
After the last post, I found that it may be fun to write a wrapper for YUI in order to make it behave like jQuery. Therefore, the code below is clearly mainly for self-amusement and is not intended to be used in production projects. However, through coding this, I found that although the difference in design, but YUI is obviously capable to do what jQuery offers (if not more). I will not continue working on this so whoever interested may just copy and paste the code to further developing it.
Long long time ago when I was working with Prolog, I was introduced to list. Unlike arrays in most popular programming languages, we weren’t really able to access to a particular member directly. Every list is constructed in a chain-like structure.