acho.io VS Prodigy

acho.io Reviews

1. Jason

   | Data analyst at Comcast | about 3 years ago
   Great for accessing huge datasets

   I use Acho for storing and editing my data files. It's amazingly fast, and intuitive to use. The dashboard is still in beta but works pretty well with the data sync feature.

   👍 Pros:    Great customer support|Great user experience|Great set of functions

   👎 Cons:    Few features are in beta

Prodigy Reviews

acho.io mentions (2)

• New Grad Tasked with Building a Data Pipeline

  The company I work at called Acho built a solution that combines ETL + DW + DMBS. If your data needs to be consumed by end production beyond SQL queries (BI, spreadsheets, reports, distribution...), it could be pretty powerful. It all depends on the production goal. If you simply want data on cloud, you probably wouldn't even need replication. Source: over 2 years ago

• What tool do you recommend for basic reporting (not visualization) from a cloud based DW? (Snowflake)

  I'd probably consider an online DB GUI like Acho for this. Not sure if they connect with Azure Blob directly. Then your stack can be BLOB landing --> Matillion 'ELT' --> Snowflake tables ---> versioned table for each team member on Acho ---> Extracts by end users (no SQL needed). Source: over 2 years ago

Prodigy mentions (25)

• 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: about 1 year 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