Great content. I've been doing freelance machine learning work for a while, and it's hit or miss. Some clients are great, others are a complete pain.
Most recent gig I had, the client cut hours and then rates... all due to the fact that the CEO didn't manage the project properly from the outset, and they were hemorrhaging cash. That fell squarely into the "not my problem" category, so I quit.
It's a tough business, and one I've not completely figured out yet.
I have been a freelancer for 10 years now, and I noticed that machine learning gigs are a bit harder to find because they is usually proprietary info and they want to keep the "models" in house.
Gigs seem to fall into a couple categories: one group of clients has heard all the buzz and wants to get in on the action, without really knowing much about it.
The more serious types are indeed protective of their data, intellectual property, and processes. I have even seen paranoia around leveraging open source frameworks (Tensorflow, Pytorch) out of fear of their sponsor corporations coming for the client... not sure I see the logic on that one, but whatever.
Whenever I don't have much success in a venture, I try to look inward to see what I'm doing wrong. I suspect that there is a fair amount I have to learn about getting good gigs and being successful in the freelance game. Unfortunately, it's one of those "have to learn the hard way" type of things.
Most recent gig I had, the client cut hours and then rates... all due to the fact that the CEO didn't manage the project properly from the outset, and they were hemorrhaging cash. That fell squarely into the "not my problem" category, so I quit.
It's a tough business, and one I've not completely figured out yet.