Notes on codes, projects and everything
I have just re-started to find myself a job as my work in mybloggercon almost come to an end (after helping them to set up an April Fool Prank). I have sent some enquiry letters to apply for a job in web-development field mostly involves PHP. I prefer PHP over ASP.NET because I can have greater flexibilities in developing in PHP as what I experienced when I was developing my final year project.
After a year and half, a lot of things changed, and annoy also changed the splitting strategy too. However, I always wanted to do a proper follow up to the original post, where I compared boosting to Annoy. I still remember the reason I started that (flawed) experiment was because I found boosting easy.(more…)
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.
Sometimes, letting a piece of code evolving by itself without much planning does not usually end well. However I was quite pleased with a by-product of it and I am currently formalizing it. So the by-product is some sort of DSL for a rule engine that I implemented to process records. It started as some lambda functions in Python but eventually becomes something else.
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.
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.