At first I was confused why this was being posted after the event. Turns out all the videos are now online and freely accessible from the lectures. Pretty cool!
A word of caution - these talks are highly technical and theoretical and I don't recommend them for anyone looking to understand practical applications of ML. If, however, you're interested in intro to cutting edge work at the frontier of theoretical underpinnings of ML, this is a fabulous group talks from some of the sharpest academics in the field.
For me, a tutorial implies that students will attempt to practice the skill and the instructor is there to help with the practical aspects, and explain how to solve actual problems. It has to be interactive, and it has to involve solving specific problems rather than just talking about general ideas.
I find it very confusing when I come across all these "tutorials" on deep learning, reinforcement learning, etc. They just seem to be general lectures without any actionable instructions or practical guidance.
Am I missing some part of what happens when I look at these recordings, or does the word "tutorial" mean something different in the ML community?
I think generally tutorial is a broader term than you're refering to. I've never really thought about it, but the first "php tutorials" and "javascript tutorials" I ever looked at were tutorials, so were the instructor-led practical machine learning classes at university.
Wikipedia says "A tutorial can be taken in many forms, ranging from a set of instructions to complete a task to an interactive problem solving session (usually in academia)." - which seems to encompass everything from online tutorial explanations, to online video courses, to academia itself. That matches my experience with tutorials anyway.
I've noticed the same thing. I would guess it happens because most of the authors of these resources work in academia, and "practical" might mean different things to a researcher versus an engineer.
