2015 May

• #nand2tetris is fun

  The Nand2Tetris part I at coursera is very much my first completed course. It was so fun to actually work through the material and it feels amazing to know how simple it is to actually build a computer from scratch. While it is simple, it doesn’t mean the course itself is easy though. I was struggling to get the CPU wired up properly that I spent two to three days just to get it working.

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Random Posts

• Sorting Multilingual Data

  Been trying my best to stick to the well-known UNIX Philosophy – “Do one thing and do it well”, so I have been breaking down my projects into numerous pieces of small tasks and rely on existing tools whenever possible. One of the existing tool that I use a lot is the GNU sort tool. Generally sort utility is really doing fine and dandy without having to configure anything, at least not until I realize the problem that leads to this post.

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• Estimating the value of pi with a line of Python

  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.

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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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• Extending Zend Framework

  I like how Kohana 3 organizes the classes, and I thought the same thing may be applied to my Zend Framework experimental project. Basically what this means is that I can name the controller class according to PEAR naming convention, and deduce the location of the file by just parsing the class name.

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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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