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.
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.
A friend of mine recently posted a screenshot containing a code snippet for a fairly straight forward problem. So after reading the solution I suddenly had the itch to propose another solution that I initially thought would be better (SPOILER: Turns out it isn’t). Then mysteriously I stuck myself to my seat and started coding an alternative solution to it instead of playing Diablo 3 just now.
Semantic Web is not just about putting data on the web, but also making links to allow a person as well as a machine to explore the web of data. Links are made in the web of data connects arbitrary things together as described by RDF as opposed to links in the web of hypertext, where links connects to only web-resources. Linkage of arbitrary things then allow related things to be found while performing search.
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.
Should have done this earlier, I was just being lazy to go through all the steps to publish it properly. So here it is, the full source is published to bitbucket. Feel free to fork the project if you are interested. I have not attach a licence to it but it will most probably be BSD licence. I have also uploaded the latest 0.0.2 release to bitbucket and would update the download link posted previously soon.