[squarefoot]

As someone who got only his feet wet with OpenCV like 20 years ago, so basic shape recognition and no AI involved, what read/software, etc. would you suggest to catch up and play with current technology without being inundated by theory that I'm sure I couldn't grasp?

[montanalow]

Go to huggingface.com and start with some of the tutorials. The operational/engineering skill sets alone are all you need to treat modern ML models like any other black box API/SDK.

[intpx]

They call it ‘Tasks’

https://huggingface.co/tasks

[Tempest1981]

https://huggingface.co (no 'm')

[synergy20]

went there and there are lots of stuff indeed, but I failed to find anything related to "operational/engineering skill sets"?

[mdda]

To just play with something : https://huggingface.co/spaces/nateraw/yolov6 (There's an images tab, and some samples below).

If you go to the associated code, you'll see that it needs a 'backbone', 'neck' etc. What is a backbone? Questions that arise directly from the code will lead you towards good blog articles, etc. https://huggingface.co/spaces/nateraw/yolov6/blob/main/yolov...

OTOH, you could go and have a look at (for instance) the Stanford vision courses for a more 'theoretical' approach. But the code itself is often solid guide to what's going on (the frameworks used for Deep Learning map well onto what's being discussed in blogs/lectures/papers).

[bj-rn]

MS put up some courses on github: https://microsoft.github.io/ML-For-Beginners

https://microsoft.github.io/AI-For-Beginners/

[bigdict]

Start with theory you're sure you could grasp. Understand how convolutions work and that covers a good chunk of theory.

Here's a good resource: https://eli.thegreenplace.net/2018/depthwise-separable-convo....