deep-significance
Enabling easy statistical significance testing for deep neural networks. (by Kaleidophon)
Note
Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, CLIP, ViT, ConvNeXt, SwiftFormer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow. (by NoteDance)
| deep-significance | Note | |
|---|---|---|
| 6 | 48 | |
| 316 | 35 | |
| - | - | |
| 4.0 | 9.9 | |
| 7 months ago | 3 days 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)
Note
Posts with mentions or reviews of Note.
We have used some of these posts to build our list of alternatives
and similar projects.
- Easily implement parallel training.
- This project allows you to easily implement parallel training with the multiprocessing module.
-
Train neural networks in parallel using Python's multiprocessing module.
https://github.com/NoteDancing/Note This project allows you to train neural network in parallel using Python's multiprocessing module.
- A system for deep learning and reinforcement learning.
- A system for deep learning and reinforcement learning. (r/MachineLearning)
- [P] A system for deep learning and reinforcement learning.
What are some alternatives?
When comparing deep-significance and Note you can also consider the following projects:
nannyml - nannyml: post-deployment data science in python
deep-RL-trading - playing idealized trading games with deep reinforcement learning