2016

• Approximate Neighbour Search in Multiple Dimensions

  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.

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• Re-implementing Approximate Nearest Neighbour Search

  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.

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• Information Retrieving with ….. a lot of libraries

  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.

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Random Posts

• Over-doing a task: reading CSV file in #golang

  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”.

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• Building a simple ASGI Websocket Application

  Getting comfortable to asyncio takes a bit of practice, so I revisited a practice project I did when I was working for my previous company. Suppose I want to build a very simple websocket application, without use of any web application library/framework. In order to keep it simple, I also opt to just build the frontend with minimal setup (just plain ES6 without webpack/vite).

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• Gotta start working

  After delaying for quite some time, I think I should start the project before I get bored with it. The project will be either hosted on this current domain (coolsilon.com) at least for now and will probably move to another domain if needed. The site will be either a blog aggregator or just a simple article submission site that works kinda like digg / reddit, however, to be promoted to the frontpage the submission would have to impress the opposite group.

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• Processing JSON with dask.bag

  Often times, I am dealing with JSONL files, though panda’s DataFrame is great (and blaze to certain extend), however it is offering too much for the job. Most of the received data is in the form of structured text and I do all sorts of work with them. For example checking for consistency, doing replace based on values of other columns, stripping whitespace etc.

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• Quick experiment, boosting vs annoy

  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.

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