Most users struggle to see the full value of a product within the first 14 days (if ever).
That's why we built UserGuiding, a no-code product adoption platform that helps increase activation & retention and reduce churn using many in-app walkthroughs and widgets as well as standalone Knowledge Base and Product Updates pages. Provide your users all the self-serve help they need throughout their journey, and also gather valuable insights and feedback from them with our in-app surveys to give you direction and improve your product development.
The best part? You can do it all without breaking the bank and with zero technical expertise, thanks to our drag-and-drop interface.
Try UserGuiding today to give your product adoption a huge, instant boost.
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Based on our record, YOLO should be more popular than UserGuiding. It has been mentiond 14 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I do some work with https://userguiding.com/ and I find them to be a good compromise between features and pricing. It's one of the more affordable user onboarding platforms out there but comes in packed with functionalities, and it looks nice, too. Source: over 2 years ago
Use user guides to onboard customers flawlessly (https://userguiding.com/). Source: over 3 years ago
OpenCV and "AI" can work well together; see YOLO: https://pjreddie.com/darknet/yolo/. - Source: Hacker News / 7 months ago
Then there is the creator of YOLO. His resume is epic. It's completely My Little Pony themed. Source: almost 2 years ago
For the API, I've used python and django. For image processing and detecting persons in image, I used yolov3. If any person exceeded limit that user gave, the API sends notification to user via telegram. Source: almost 2 years ago
The paper says the source code is available: Https://pjreddie.com/darknet/yolo/. Source: about 2 years ago
If you are trying to identify objects in an image (like 'cat', 'person', etc), then you might look at YOLO. There are lots of github projects using it to explore, too. Source: over 2 years ago
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