Prodigy
Enovia
Propel
Omnify PLM
Arena PLM
SLIM Suite
aPriori
Centric Software
Amazon Machine Learning
Machine Learning Playground
Apple Machine Learning Journal
Lobe
ML5.js
Apple Core ML
Google Cloud Machine Learning
Azure Machine Learning Service
Based on our record, Prodigy seems to be a lot more popular than Amazon Machine Learning. While we know about 25 links to Prodigy, we've tracked only 2 mentions of Amazon Machine Learning. 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 / over 1 year 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 / over 1 year ago
Prodigy AI - Offers software engineers career coaching, skill assessment, and job matching. Visit Prodigy AI. - Source: dev.to / almost 2 years 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 2 years 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 2 years ago
There’s also the ML as a service (MLaaS) movement that lowers the barrier for common ML capabilities (eg image object detection and audio transcription). Basically, you use APIs. See: https://aws.amazon.com/machine-learning/. Source: over 2 years ago
Do you have questions about Data Science and ML on AWS - https://aws.amazon.com/machine-learning/. Source: about 4 years ago
Enovia - ENOVIA offers product lifecycle management (PLM) solutions fostering innovation and operational excellence across industries.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Propel - Salesforce-native PLM, QMS, and PIM. Connect your product and commercial teams seamlessly to create winning products.
Apple Machine Learning Journal - A blog written by Apple engineers
Omnify PLM - Omnify PLM is a business-ready product lifecycle management solution.
Lobe - Visual tool for building custom deep learning models
