Notes on codes, projects and everything
gensim
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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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Packaging a Daemon Script for Meego 1.2 Harmattan
Another half a day spent on figuring out how to package my daemon properly, fortunately with help from friends over at #harmattan IRC channel as well as cckwes, I finally get the deb package generated properly. So just a quick reminder on what my daemon does, it is just a quick hack that toggles the ‘allow background connections’ on and off depending which kind of data network a user is connected to. Apparently I am not the only one who are looking for this, as a feature request was filed long long time ago.
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Symlinking two Blogs
I am currently doing some organization to my blogs. Few weeks ago, after spending months struggling to work in Ubuntu 7.10, I learned about symbolic links. Then I thought this would be good for my project file management. Therefore I started to re-organize my project file structure to utilize symbolic links. One of the projects that uses symbolic link is the current wordpress theme.
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The Little Pythoner, Part 2
In the last part, I implemented a couple of primitive functions so that they can be applied in the following chapters. The second chapter of the book, is titled “Do it again, and again, and again…”. The title already hints that readers will deal with repetitions throughout the chapter.
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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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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.
