Plurrrr

Graph Neural Networks were introduced back in 2005 (like all the other good ideas) but they started to gain popularity in the last 5 years. The GNNs are able to model the relationship between the nodes in a graph and produce a numeric representation of it. The importance of GNNs is quite significant because there are so many real-world data that can be represented as a graph. Social networks, chemical compounds, maps, transportation systems to name a few. So let’s find out the basic principles behind GNNs and why they work.

Most IT firms where I worked as programmer were IT services industry, there was very little greenfield work and most of the time we had to maintain/fix code written by other engineers who couldn't even be found in some cases!

As a result, reading and debugging existing code was something we had to adapt ourselves to. Based on my experience, this is a brief overview of how the process generally works and some tricks to make your life easier:

If you learn about lxc, you can integrate generic Linux containers into your own system design to solve whatever problem you think a container can solve.

Interfaces in Go are a topic that tend to trip up people coming from a variety of languages like Java or C#. The oddest thing about them is probably that interfaces are implicit rather than explicit . So whereas in most languages there is some type of syntax or a keyword to say you’re implementing an interface, there’s no such thing in Go.

Another difference is that good interfaces in Go should be small — they should contain only a few methods. I know how tempting it is to just add one more method to an interface, and have them grow organically like that. This does create some downsides in terms of having others use your interface and refactor work if you change them later.