Based on our record, Papers with Code should be more popular than Prodigy. It has been mentiond 96 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.
This is really cool. The annotation-to-testing-to-annotation-etc. Feedback loop makes a ton of sense, and I'd encourage others who may be confused on this post to look at the Automotus case study https://encord.com/customers/automotus-customer-story/ for the annotation side, but my understanding is the relationship between model outputs and annotation steering is out of scope for that project - do you know of... - Source: Hacker News / 3 months ago
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post. The steps... - Source: Hacker News / 8 months ago
Prodigy AI - Offers software engineers career coaching, skill assessment, and job matching. Visit Prodigy AI. - Source: dev.to / 9 months ago
I essentially want to use a Combo of OCR + NER to attempt to identify this, but I'm not sure NER is well suited for this, as it is not natural language, so there is little context to go off of. I was thinking of perhaps using Prodigy, a data annotation tool, to annotate Candidate Names, Races, etc, and perhaps it will be able to learn off of image data alone wheat these fields tend to look like. Source: about 1 year ago
I come from a similar application area, where I try to tag (annotation/label) a taxonomy of products iteratively. You are trying something slightly different, AFAIU, labeling a flat set of songs, each song with a set of tags from ontology (directed graph)From an application point of view, this is what taxonomists often do, when migrating products from one catalog to another: mapping one taxonomy to another. There... Source: over 1 year ago
Papers With Code is one of the good resources to get you to get started. - Source: dev.to / 18 days ago
For ML/DL papers you can check https://paperswithcode.com/. - Source: Hacker News / 4 months ago
This resource has been invaluable to me: https://paperswithcode.com/ From the past examples you give it sounds like you were into computer vision. There’s been a ton of developments since then, and I think you’d really enjoy the applications of some of those classic convolutional and variational encoder techniques in combination with transformers. A state of the art multimodal non-autoregressive neural net model... - Source: Hacker News / 5 months ago
And also you can find papers with their implementations in code here: http://paperswithcode.com. - Source: Hacker News / 5 months ago
Check out paperswithcode, scroll through arxiv, or browse some well-known conferences in the field (NeurIPS, ICML). Source: 5 months ago
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