#algorithm complexity

Went to my second ever hackathon today! ... Well, I was there for a couple of hours at least. It was the first hackathon at the company where I work, and (un)surprisingly there was a lot of technical issues, in that the Wi-Fi was nearly impossibly to use. And when we were connected, it was just mind-numbingly slow. My team and I wanted to use a Myo to control a Parrot Drone and then we would figure out the rest from there, but it just became too difficult to work and progress was just so slow that we up and left. 

On the bright side, we did manage to get the drone and the Myo working individually! It was really cool using the drone from the FreeFlight app, and then it wasn’t much more effort to send it commands from a laptop. I was pretty surprised that drone files are written in Node.js? I really need to learn more about that language, I hear people talking about it all the time but I don’t know anything about it. We also got the Myo working with their pre-installed software - I didn’t get the chance to really play with it, but that’s also on my to-do list.

When I got home, I spent some time reviewing algorithm complexity, specifically Big Theta notation and the difference between that and Big O. I never learned about Big Theta in class and they seem pretty similar so I guess the idea is still kinda jangled in my head. 

I’ve started reading Introductions to Algorithms by Cormen -- it’s so highly recommended, I’ll make a separate post to a PDF later, specifically Chapter 2 today.