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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
by squarefoot 4y ago
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 4y agoGo 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.
- Tempest1981 4y agohttps://huggingface.co https://huggingface.co (no 'm')
- synergy20 4y agowent there and there are lots of stuff indeed, but I failed to find anything related to "operational/engineering skill sets"?
- intpx 4y agoThey call it ‘Tasks’ https://huggingface.co/tasks https://huggingface.co/tasks
- bigdict 4y agoStart 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-convolutions-for-machine-learning/ https://eli.thegreenplace.net/2018/depthwise-separable-convo....
- mdda 4y agoTo just play with something : https://huggingface.co/spaces/nateraw/yolov6 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/yolov6/models/yolo.py#L34 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 4y agoMS put up some courses on github: https://microsoft.github.io/ML-For-Beginners https://microsoft.github.io/ML-For-Beginners https://microsoft.github.io/AI-For-Beginners/ https://microsoft.github.io/AI-For-Beginners/