I have officially become a PhD candidate, so the next three years will be rough. The quantity of projects I work on is likely to decrease due to the required focus. Needless to say, I will not have much to show for the next few seasons. Hopefully, if all goes well, at the end of it all, it will more than make up for it.
Continuing with the theme established by last season, my recommendation is Mr. Nobody. Mr. Robot, Mr. Nobody, Mr. Axilus… definately not a coincidence, right? Anyway, watch the movie, in a way it is like The Matrix, but in reverse.
My accomplishments this season should be able to speak for themselves. It brings me pleasure to announce that I:
- obtained a Masters degree in machine learning,
- started a Doctorate degree in artificial intelligence,
- and experimented with OpenGL in Nim.
Wrapping up the year, my recommendation is the series Mr. Robot. I have a bias towards stories that mess with the consumer, but Mr. Robot is special. The hacking methods employed in the show actually align with reality. Watch this show, even if it is just to see what non-hollywood hacking is like.
This summer I continued producing projects for my Masters such as:
- anlysing the genome of the Bermuda Longtail,
- creating a simple SPDY proxy sever,
- and tracking feet positions from a RGB CCTV camera.
As always, my seasonal recommendation is the book series Blindsight. I must warn you, it is super hard Sci-Fi, but for those like me, it is refreshing. Peter Watts goes so far as to base the world on plausible scientific theories.
My focus is still consistently devoted to obtaining my Masters. This time around my projects involved:
- performing basic programing in Prolog,
- starting to gather literature for thesis,
- and simulating a student marking session using C.
For this spring, my recommendation would be the fictional book Worm. I normally dislike generic fictional worlds, but man does this break preconceptions. Worm has super heroes that actually think, and I mean really THINK. It is quite long but if I could read it again for the first time, I would.
My Masters course at the University of Bristol continued unremittingly. The assignments proved themselves to be a greater challenge than expected. Do not get me wrong, this is not necessarily a bad thing. In fact, these projects have given me some of my greatest learnings. Amongst others, this season’s assignments included:
- building a image-based object detector using the Viola-Jones framework,
- predicting the availability of bike spaces using machine learning,
- and creating a cloud-based web application on Google App Engine.
This season my recommendation is Nudge. Nudge draws on behavioural economics to provide, in my opinion, a significant insight. That insight is labelled choice architecture. It is a bit too much to describe here, but read it, see for yourself.
September marked the start of my Masters degree at the University of Bristol. A degree entitled Machine Learning, Data Mining, and High Performance Computing. A bit of a mouthful, but reasons exist for this particular choice. My interest in the fields of data science and artificial intelligence built up over time. A kind of interest akin to an ocean wave breaking upon the shore. A wave which was there all along, but only became visible and tall when it reached its destination. A point by which you, the beachgoer, get smacked in the chest and taken by surprise. That’s kind of what happened with me, one day making the decision that this is what I wanted to do.
My recommendation of the season is You Are Not So Smart (YANSS). YANSS covers human behaviour, with a focus on the biases which affect our everyday lives. David McRaney presents content in such an inspiring way.