Notes on codes, projects and everything
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.
As the name implies, Resource Definition Framework, or RDF in short, is a language to represent information about resources in world wide web. Information that can be represented is mostly metadata like title (assuming the resource is a web-page), author, last modified date etc. Besides representing resource that is network-accessible, it can be used to represent things that cannot be accessed through the network, as long as it can be identified using a URI.
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.
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.
Recently I am involved in developing some small modules for a enterprise class website using CodeIgniter (CI). There was no restriction given on which framework should I use for the development and I chose CI as I learned a bit on it (when I was considering whether to shift my personal development project). Of course there are other reasons why I chose to learn CI, for example the superior documentation and screencasts available.
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.
Usually I take about a week to learn a new language so I can start doing some real work with it. After all a programming language (at least the high level and dynamic ones) is just assignment, calculation, branching, looping and reuse (and in certain cases, concurrency/parallelism, not gonna dive deep in defining the difference though). Well, that was true until I started learning Rust, partly for my own leisure.