deep-significance
Enabling easy statistical significance testing for deep neural networks. (by Kaleidophon)
ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models (by ludwig-ai)
Our great sponsors
| deep-significance | ludwig | |
|---|---|---|
| 6 | 3 | |
| 315 | 10,778 | |
| - | 1.6% | |
| 4.0 | 9.5 | |
| 6 months ago | about 23 hours ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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.
deep-significance
Posts with mentions or reviews of deep-significance.
We have used some of these posts to build our list of alternatives
and similar projects.
- [P] deep-significance: Enabling easy statistical significance testing for deep neural networks
-
[D] Statistical Significance in Deep RL Papers: What is going on?
Because I was so frustrated by this topics as well, I actually reimplemented and packaged a test specifically for NNs and gave it a lot of documentation in the hope of lowering the entry barrier as much as possible https://github.com/Kaleidophon/deep-significance
- deep-significance: Easy and Better Significance Testing for Deep Neural Networks
- [P] deep-significance: Easy and Better Significance Testing for Deep Neural Networks
- [Project] deep-significance: Easy and Better Significance Testing for Deep Neural Networks (link below)
- [P] deep-significance: Easy and Better Significance Testing for Deep Neural Networks (link below)
ludwig
Posts with mentions or reviews of ludwig.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-07.
-
Show HN: Toolkit for LLM Fine-Tuning, Ablating and Testing
This is a great project, little bit similar to https://github.com/ludwig-ai/ludwig, but it includes testing capabilities and ablation.
questions regarding the LLM testing aspect: How extensive is the test coverage for LLM use cases, and what is the current state of this project area? Do you offer any guarantees, or is it considered an open-ended problem?
Would love to see more progress toward this area!
-
Python projects with best practices on Github?
Two random examples I found from 30 seconds of googling: Here’s Netflix using it in their crisis management tool, and here’s Uber using it in their deep learning framework.
-
Most Frequent 600 Coding Questions on LeetCode
They list themselves all over the internet as an "open source contributor" to Uber, which as far I can tell is based entirely on... reporting that there was an issue with a favicon. To me, it seems like they'll be cheating anybody who employs them based on this, ahem, "experience". And that feels like the tip of the iceberg.
What are some alternatives?
When comparing deep-significance and ludwig you can also consider the following projects:
nannyml - nannyml: post-deployment data science in python
nlp-recipes - Natural Language Processing Best Practices & Examples