Prodigy Reviews and details

Social recommendations and mentions

• Launch HN: Encord (YC W21) – Unit testing for computer vision models

  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

• Against LLM Maximalism

  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

• Remote Work 2.0: The Tools, Trends, and Challenges of the Post-Pandemic Work Era

  Prodigy AI - Offers software engineers career coaching, skill assessment, and job matching. Visit Prodigy AI. - Source: dev.to / 9 months ago

• [D] A model to extract relevant information from a Sample Ballot.

  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: 12 months ago

• Sampling leaves from a tree

  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

• Labelling Tweets for NLP Project through crowdsourcing

  Not cheap, but spaCy has an annotation tool specifically for this purpose: https://prodi.gy/. Source: over 1 year ago

• Vertex AI: Is there a quick way to label images for model training?

  If you have the budget for a paid tool, I highly recommend giving https://prodi.gy a try, especially if you are a big python user. It can be scripted and customized using python so you can do all kinds of cool things with it. It's what I use for labelling and I'm really happy with it. Source: over 1 year ago

• Plug and Play Computer Vision in a box without coding, is that a thing?

  For annotation, check out prodigy: https://prodi.gy. Source: over 1 year ago

• Best open source annotation tool for NLP?

  Label studio has lots of options, but I've found it slow to annotate. I've tried doccano briefly, can't remember the specific issue, but wasn't a fan. I think if you're doing lots of annotations, the time savings using prodi.gy are well worth it. Annotating is so much quicker. Source: over 1 year ago

• Ask HN: Any open source text editors with word tagging?

  I worked at a place where we developed a system for doing this kind of tagging but it was for making training sets and there was no expectation that you could export the document from the system for normal use. Quite a few NLP annotation systems are out there https://prodi.gy/ https://brat.nlplab.org/ https://doccano.herokuapp.com/. - Source: Hacker News / over 1 year ago

• Launch HN: Dioptra (YC W22) – Improve ML models by improving their training data

  P.S. Not trying to compare the product or the company/team, but was hoping for a more technical understanding. How do u compare between Aquarium, HumanLoop, Cord.Tech, Lightly, https://prodi.gy/ (which is open source) and you guys ? I generally term this space as "algorithmic labeling" and there are many approaches here - https://paperswithcode.com/paper/machine-learning-algorithms-for-data-labeling. - Source: Hacker News / almost 2 years ago

• Ask HN: Implementing Licensing for a Python Application

  One very successful application I know is Prodigy (https://prodi.gy/) from explosion.ai, but I don't know how exactly they implement counting installations etc. - Source: Hacker News / almost 2 years ago

• Is there a Gui based tool to go trough databases for cleaning and validation?

  There's an annotation tool called prodigy - https://prodi.gy/. Source: over 2 years ago

• Any tools to help with labeling your own data set?

  One of the more popular tools is this by the guys over at Spacy https://prodi.gy/. Source: over 2 years ago

• Best open source/paid automatic speech labeling solution/product?

  Might be difficult to do a fully-automated solution, you'd still want to do some manual labelling to get quality data. My suggestion is to use Prodigy (disclosure: I work here). You can even bootstrap your annotation process with another model so that you won't label from scratch. Source: over 2 years ago

• [D] Extract text from classification

  If your address comes in different forms and shapes then you won't go too far with a regex so NER seems like a viable approach here . The downside is that you need quite a few labelled address data which is hard to find, or time consuming to label. If you really want to go down this path you would need to find a labelling framework, I remember that my team used prodigy a couple of years ago but there might be... Source: over 2 years ago

• Detect words based of context

  In addition to Flair you can also use SpaCy in conjunction with Prodigy as this is a fairly standard use of that toolkit. Source: over 2 years ago

• Launch HN: Lightly (YC S21): Label only the data which improves your ML model

  Having built a model to identify sensitive data having a solid data labeling solution would be awesome. https://github.com/capitalone/DataProfiler In this space, Prodigy really dominates: https://prodi.gy/ We actually built our own internal system which integrates and can export the labels (does predictive labeling, etc). Of course, we only focused on text data at the moment. - Source: Hacker News / over 2 years ago

• Show HN: An annotation tool for ML and NLP

  Hey HN! Markup is an open-source annotation tool for transforming unstructured documents into a structured format that can be used for ML, NLP, etc. Markup learns as you annotate in order to speed up the process by suggesting complex annotations to you. There are also a few different in-built tools, including: - A data generator that helps you to produce synthetic data for training the suggestion model - An... - Source: Hacker News / almost 3 years ago

• How often is NER (named entity recognition) a process in your model building process?

  Https://prodi.gy used for annotating for spacy. Source: almost 3 years ago

• Can't connect to a remote MongoDB server via Python on WSL2?

  I am using Prodigy in conjunction with mondigy to annotate data stored in a remotely hosted MongoDB server. I always receive timeout errors. On OSX and Ubuntu, I do not receive timeout errors. The Conda environments are identical (aside from OSX using a different binary). Source: almost 3 years ago