Notes on codes, projects and everything
2016 January
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Further Hack on the Multi-Dimensional Approximate Neighbour Search
Traversing a tree structure often involves writing a recursive function. However, Python isn’t the best language for this purpose. Therefore I started flattening the tree into a key-value dictonary structure. Logically it is still a tree, but it is physically stored as a dictionary. Therefore it is now easier to write a simple loop to traverse it.
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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.
Random Posts
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Learning asyncio by redoing my messaging bot
I used to develop a bot, partly for work, that fetches current latest petrol retail price in Malaysia. The bot was really an experiment, but at the time it worked well. Then a few years later, out of boredom, I revisited the project after finding the telegram bot library is moving towards asyncio. It was great (at least a lot of people rave about it), but also at the same time intimidating, I learned about coroutines and used gevent in the past, but not asyncio itself.
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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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How to solve all puzzles at 4clojure in a week
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.
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Weekend Code Quiz – Easy Template Parser
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.
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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.
