Datatang.ai VS Prodigy

Data annotation is an essential step in preparing data for use in Machine Learning models. This is where Datatang.ai comes in. Our company specializes in data annotation, providing high-quality and accurate data for training autonomous vehicle machine learning models. Our team of experts works diligently to ensure that every annotation meets the required standards, and our cutting-edge technology ensures that we... Source: about 1 year ago

Data annotation is a crucial action in preparing information for usage in Machine Learning versions. This is where Datatang.ai comes in. Our company specializes in data annotation, supplying high-quality and accurate data for training self-governing car equipment learning designs. Our team of professionals functions vigilantly to ensure that every annotation meets the required requirements, and also our advanced... Source: about 1 year ago

At Datatang.ai, we realize that every project has unique needs, which is why our object tracking dataset is customizable. We work with our clients to ensure that they receive the data that they need for their specific project, whether it's for research, training machine learning models, or developing new products. Source: about 1 year ago

At Datatang.ai, we realize that every job has special needs, which is why our object monitoring dataset is adjustable. We deal with our clients to guarantee that they receive the information that they require for their particular project, whether it's for research study, training equipment learning models, or developing new products. Source: about 1 year ago

At Datatang.ai, we realize that every job has unique needs, which is why our things tracking dataset is personalized. We deal with our clients to make sure that they get the information that they need for their details job, whether it's for research study, training machine discovering versions, or developing brand-new items. Source: about 1 year ago

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