Notes on codes, projects and everything
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.
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.
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.
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.
I wanted to try using virtuoso as the storage engine for Redland but unfortunately there is no librdf-storage-virtuoso package for Ubuntu. After getting some help from @dajobe, I attempted to build the packages myself. Although it takes quite some time to build packages, but not too difficult it seems.
So my cheat with dask worked fine and dandy, until I started inspecting the output (which was to be used as an input for another script). While the script seemed to work fine, however when I started to parse each line I was hit with some funny syntax errors. After some quick inspection I found some of the lines was not printed completely.
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
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.
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.