colours-in-culture
Get the cultural meanings for a given color. (by tfrere)
pytkml
Write tests for machine learning models (by rbitr)
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colours-in-culture | pytkml | |
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1 | 3 | |
4 | 5 | |
- | - | |
10.0 | 0.0 | |
almost 4 years ago | almost 3 years ago | |
JavaScript | Python | |
MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
colours-in-culture
Posts with mentions or reviews of colours-in-culture.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-14.
pytkml
Posts with mentions or reviews of pytkml.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-26.
-
Ask HN: What have you created that deserves a second chance on HN?
Code: https://github.com/rbitr/pytkml
I didn't explain it well; this is an area that's becoming increasingly important
-
Ask HN: What is something you built but never marketed?
I worked on (wouldn't say I completed) a testing framework for ML models, where you can specify a series of tests for a model to pass. The unique part is emphasizing support from the training data for the inferences you expect the model to make, i.e. checking that similar training data exists for some test cases and is influential in predicting them. It's pretty niche, and I don't explain it very well, but I remain convinced that with the right framing it represents a more rigorous way of making sure machine learning models are built and used "responsibly".
https://github.com/rbitr/pytkml
- Show HN: Writing tests for machine learning models
What are some alternatives?
When comparing colours-in-culture and pytkml you can also consider the following projects:
ViGEmClient - ViGEm Client SDK for feeder development.
scipipe - Robust, flexible and resource-efficient pipelines using Go and the commandline
personal-gallery-node - Simple self-hosted image gallery
pdfcomments
netbase - 🌐 Netbase : Semantic Graph Database & Wikidata Server
drummachine
vgpu_unlock - Unlock vGPU functionality for consumer grade GPUs.
india-pincode-regex - A simple regex based exhaustive validator for PIN codes in India
reddit-playlists
youtube2Anki - Convert Youtube Transcripts to Anki cards
colours-in-culture vs ViGEmClient
pytkml vs scipipe
colours-in-culture vs personal-gallery-node
pytkml vs pdfcomments
colours-in-culture vs netbase
pytkml vs drummachine
colours-in-culture vs vgpu_unlock
pytkml vs india-pincode-regex
colours-in-culture vs pdfcomments
pytkml vs reddit-playlists
colours-in-culture vs youtube2Anki
pytkml vs youtube2Anki