Notes on codes, projects and everything
Back then when I was attending a job interview, I was asked to write a Fizz Buzz program to prove that my coding ability. There was only a pen and a piece of paper, so basically means there’s no way I can refer to the documentation for the API syntax. Fortunately I somehow managed to remember and not screw up.
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 was trying to learn scala and clojure to find one that I may want to use in my postgraduate project. After trying to learn scala for a couple of days, I gave up because I really don’t like the syntax (too OO for my liking). Then I continued with clojure and found myself liking the syntax better.
To do node selection for DOM operations, one typically uses CSS selectors as (probably) popularized by jQuery. However, there is another alternative that is as powerful if not better known as XPath. XPath may be able to do a lot more than just selecting node (which I have no time to find out for now) but I will just focus on how to do node selection in this blog post.
I was thinking whether it is possible to avoid exposing PDO and PDOStatement objects to the users of my database library (mainly just me). While I was working on my project I sort of notice that there is a almost fixed pattern whenever I work with the database. With this in mind, I added in some new functions to the library, and decided to make a quick release for this.
While working on a text classification task, I spent quite some time preparing the training set for a given document collection. The project is supposed to be a pure golang implementation, so after some quick searching I found some libraries that are either a wrapper to libsvm, or a re-implementation. So I happily started to prepare my training set in the libsvm format.
Recently I switched my search code to Annoy because the input dataset is huge (7.5mil records with 20k dictionary count). It wasn’t without issues though, however I would probably talk about it next time. In order to figure out what each parameters meant, I spent some time watching through the talk given by the author @fulhack.