Notes on codes, projects and everything
This is the year I kept digging my old undergraduate notes on Statistics for work. First was my brief attempt wearing the Data Scientist performing ANOVA test to see if there’s correlation between pairs of variables. Then just recently I was tasked to analyze a survey result for a social audit project.
(more…)So apparently Annoy is now splitting points by using the centroids of 2 means clustering. It is claimed that it provides better results for ANN search, however, how does this impact regression? Purely out of curiosity, I plugged a new point splitting function and generated a new set of points.
(more…)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…)A few years ago, I was asked to build a game or simulation (alongside 2048) as a part of a job application. Being very impressed with Explorable Explanations, I implemented Conway’s Game of life with Javascript and jQuery (that was before ES6 became popular). Then I made a very simple grid maker jQuery plugin to dynamically generate a grid of divs. If you check the source code, you may realize I rely on Underscore.js a lot back then.
(more…)Usually I take about a week to learn a new language so I can start doing some real work with it. After all a programming language (at least the high level and dynamic ones) is just assignment, calculation, branching, looping and reuse (and in certain cases, concurrency/parallelism, not gonna dive deep in defining the difference though). Well, that was true until I started learning Rust, partly for my own leisure.
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 finally put in some time and effort learning myself a bit of Rust. Though I am still struggling with ownership and lifetimes (which is essentially everything about the language, to be honest), I find it more interesting compared to Golang, which is relatively boring, though being functional (no pun intended). While learning the language, the one thing I came across often is the Option
enum, then I remembered that I read something about Monad.
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.
Javascript is getting so foreign to me these days, but mostly towards a better direction. So I recently got myself to learn react through work and the JSX extension makes web development bearable again. On the other hand, I picked up a little bit on Vue.js but really hated all the magic involved (No I don’t enjoy putting in code into quotes).
One of my recent tasks involving crawling a lot of geo-tagged data from a given service. The most recent one is crawling files containing a point cloud for a given location. So I began by observing the behavior in the browser. After exporting the list of HTTP requests involved in loading the application, I noticed there are a lot of requests fetching resources with a common rXXX
pattern.
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.
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.
I like how Kohana 3 organizes the classes, and I thought the same thing may be applied to my Zend Framework experimental project. Basically what this means is that I can name the controller class according to PEAR naming convention, and deduce the location of the file by just parsing the class name.
I need a slide show script for my portfolio pages but couldn’t find a good one anywhere so I decided to write one myself. The slide show script will be able to display image and the respective description in a predefined order. However, in this version, visitors would not be able to directly jump to a particular slide yet. The script is written in prototype‘s object-orientation approach hence you need to have prototype called.
I saw this article from alistapart, which is about Javascript’s prototypal object orientation. So the article mentioned Douglas Crawford, and I was immediately reminded about my struggle in understanding the language itself. Back then I used to also refer to his site for a lot of notes in Javascript. So I went back to have a quick read, and found this article that discusses the similarity between Javascript and Lisp.