Notes on codes, projects and everything
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).
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.
I have recently made my Adium useless by moving all my IM accounts to my beloved Nokia N9. While moving my buddy lists of all major instant messaging services, I did a quick check on each of the contact to see past interaction. It is sort of surprising to see I don’t actually chat with them as frequent as I thought, so why do I “need” my Adium opened all the time?
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.
In the previous post, I re-implemented Annoy in 2D with some linear algebra maths. Then I spent some time going through some tutorial on vectors, and expanded the script to handle data in 3D and more. So instead of finding gradient, the perpendicular line in the middle of two points, I construct a plane, and find the distance between it and points to construct the tree.
This is the formal draft of my statistical analysis report for the social audit project previously mentioned here. As the project is public by nature, I am cross-posting here for own reference.
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