Notes on codes, projects and everything
Sometimes I really doubt about the advantage of recycling old stuff to fund for new units beyond goodwill. Sure you get to convince yourself that you are saving the environment by doing so, and it also saves money in the long run. However, I didn’t realize how much it generates it may be after trying to work out an answer for a fictional IQ question.
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).
With most of my stuff more or less set, I guess it is time to start documenting the steps before I forget. So I heard a lot of good things about docker for quite some time, but haven’t really have the time to do it due to laziness (plus my relatively n00b-ness in the field of dev-ops). Just a few months ago, I decided to finally migrate away from webfaction (thanks for all the superb support) to a VPS so I can run more things on it.
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.
This is the second part of the golang learning rant log. Previously on (note (code cslai)) I managed to make each line in the CSV into a hash map. So today I am going to make it into JSON Lines.
I was invited to try Go (the programming language, not that board game) a few months ago, however I didn’t complete back then. The main reason was because it felt raw, compared to other languages that I know a fair bit better (for example Ruby). There was no much syntatic sugar around, and getting some work done with it feels “dirty”.
A new day, and a new post on job application. So this time instead of asking a snippet, I was actually asked to deliver some sort of a full application. Not sure why this was required, but I had fun creating them nonetheless. Though I would say I am not really a fan of creating visual stuff though (oh the crappy animation nearly killed me).
Another day, another programming assessment test. This time I was asked to generate some random data, then examine them to get their data type. Practically it is not a very difficult thing to do and I could probably complete it in fewer lines. I am pretty sure there are better ways to do this, as usual though.
I just failed a programming assessment test miserably yesterday and thought I should at least document it down. However, the problem with this is that the questions are copyrighted, so I guess I would write it from another point of view. So the main reason I failed was because I chose the wrong strategy to the problem, thinking it should be solution but as I put in time to that I ended up creating more problems.
The Nand2Tetris part I at coursera is very much my first completed course. It was so fun to actually work through the material and it feels amazing to know how simple it is to actually build a computer from scratch. While it is simple, it doesn’t mean the course itself is easy though. I was struggling to get the CPU wired up properly that I spent two to three days just to get it working.
Back then in college, we were given a lot of programming practices. These questions usually shows a desired output format, and we were required to write a program to print out the exact thing. Usually it involves printing a matrix of numbers, or symbols etc. For these problems, usually a loop structure or two should solve the problem.
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.
It is very much expected that there will be endless stream of new (and often times better) tools introduced to solve the same set of problems. While I am slowly resuming my programming work, and in the process of reviving my very much dead postgrad project, I found some alternative to the tools I had used in the past. I suppose I shall just jot them down here so that there’s a reference for later use.
Traversing a tree structure often involves writing a recursive function. However, Python isn’t the best language for this purpose. Therefore I started flattening the tree into a key-value dictonary structure. Logically it is still a tree, but it is physically stored as a dictionary. Therefore it is now easier to write a simple loop to traverse it.
I am currently doing some organization to my blogs. Few weeks ago, after spending months struggling to work in Ubuntu 7.10, I learned about symbolic links. Then I thought this would be good for my project file management. Therefore I started to re-organize my project file structure to utilize symbolic links. One of the projects that uses symbolic link is the current wordpress theme.