2020 December

• Refreshing the ReactJS Internet Censorship Dashboard (and Dockerizing Poetry Projects)

  The Internet Censorship Dashboard is a project that aggregates data fetched from the OONI API, to provide an overview of the current state of Internet Censorship experienced by users mainly in Southeast Asia. The current form was built a couple of years ago, and recently got funded to get it updated to work better with new APIs.

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• Revisiting semantic web (plus wheel building with Poetry)

  Back then, when I was still working on my postgraduate degree research, I used RDF, which was the preferred format in the world of Semantic Web to represent data. I eventually dropped the degree, and stopped following the development of the related technology and standards. Until I volunteered to update the import script for popit when I was looking for the next job/project.

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• Working Environment Setup, for 2020

  In recent years, I start to make my development environment decouple from the tools delivered by the package manager used by the operating system. The tools (compiler, interpreters, libraries etc) are usually best left unmodified so other system packages that rely on them keeps working as intended. Also another reason for the setup is I wanted to follow the latest release as much as possible, which cannot be done unless I enroll myself to a rolling release distro.

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• 4 Fundamental Things in Programming (pre-101)

  Just recently I volunteered to do a pre-101 kinda workshop for people wanting to learn programming. I had done this a few times in the past, but in different settings and goals in mind. The whole structure predates the sessions but I can’t remember when I first created them.

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• Picking Up Category Theory (and eventually Haskell)

  I don’t quite remember when did I first heard about Category Theory, but the term stuck in my head for quite a while. Eventually I attempted to start looking for tutorials on the topic, but it is hard to find one that I actually understand. Most of them are either leaning too much to the Mathematics side, or too much to the Programming side.

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• Performing Statistical Analysis with Python

  This is the year I kept digging my old undergraduate notes on Statistics for work. First was my brief attempt wearing the Data Scientist performing ANOVA test to see if there’s correlation between pairs of variables. Then just recently I was tasked to analyze a survey result for a social audit project.

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Random Posts

• Linked Data Principle

  Semantic Web is not just about putting data on the web, but also making links to allow a person as well as a machine to explore the web of data. Links are made in the web of data connects arbitrary things together as described by RDF as opposed to links in the web of hypertext, where links connects to only web-resources. Linkage of arbitrary things then allow related things to be found while performing search.

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• Hitting a nail with the wrong hammer (my writing tools)

  I just failed a programming assessment test miserably yesterday and thought I should at least document it down. However, the problem with this is that the questions are copyrighted, so I guess I would write it from another point of view. So the main reason I failed was because I chose the wrong strategy to the problem, thinking it should be solution but as I put in time to that I ended up creating more problems.

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• Refreshing the ReactJS Internet Censorship Dashboard (and Dockerizing Poetry Projects)

  The Internet Censorship Dashboard is a project that aggregates data fetched from the OONI API, to provide an overview of the current state of Internet Censorship experienced by users mainly in Southeast Asia. The current form was built a couple of years ago, and recently got funded to get it updated to work better with new APIs.

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• Regression with Annoy (cont’d)

  After a year and half, a lot of things changed, and annoy also changed the splitting strategy too. However, I always wanted to do a proper follow up to the original post, where I compared boosting to Annoy. I still remember the reason I started that (flawed) experiment was because I found boosting easy.

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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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