ViGEmClient
ViGEm Client SDK for feeder development. (by nefarius)
pytkml
Write tests for machine learning models (by rbitr)
ViGEmClient | pytkml | |
---|---|---|
1 | 3 | |
119 | 5 | |
- | - | |
0.0 | 0.0 | |
8 months ago | almost 3 years ago | |
C | 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.
ViGEmClient
Posts with mentions or reviews of ViGEmClient.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-14.
-
Ask HN: What is something you built but never marketed?
I didn't build it, but there's ViGEm for creating virtual Xbox 360 controllers: https://github.com/ViGEm/ViGEmClient
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?
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