Summer Reading: Distributed Computing
Prompted by some of my current tasking at work, I went on a journey through Google’s history of research publications. Come join me on my quest to become a better back-end developer!
Prompted by some of my current tasking at work, I went on a journey through Google’s history of research publications. Come join me on my quest to become a better back-end developer!
Consistent incremental progress is, most of the time, just as good as occasional massive advancement. So, in the spirit of New Year’s Eve and all associated traditions, I’ve chosen to rethink how I go about the new year.
Below is a pseudo-outline of mixed advice, tricks, and links that should give you a fighting chance in any technical interview. Remember, interviewers aren’t out to get you.
Artificial Intelligence is, as a field of study, larger than Machine Learning. In fact, ML is just a specific subset of AI. I wasn’t too clear on where exactly the line was drawn, but it turns out the accepted industry answer is that you can have AI without ML, but whenever you’re doing ML, that’s a form of AI.
Knowing more about the internals of a problem can lead to better understanding and discussion across the board. Most algorithms that you’ll come across in practice aren’t going to be as simple as to fit into any one of these categories, but understanding the pieces of them allows you to get a better grasp of the system as a whole.