ML_twitter_celebs
Machine Learning project that given a dataset of tweets posted on twitter by certain peoples, learner predicts which person tweeted what. (by luko007)
tsuki-wscp
Web scraper for AI/ML training (by Tsujimar)
| ML_twitter_celebs | tsuki-wscp | |
|---|---|---|
| 1 | 2 | |
| 0 | 32 | |
| - | - | |
| 0.0 | 5.9 | |
| 10 months ago | 9 months ago | |
| Python | Python | |
| - | 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.
ML_twitter_celebs
Posts with mentions or reviews of ML_twitter_celebs.
We have used some of these posts to build our list of alternatives
and similar projects.
tsuki-wscp
Posts with mentions or reviews of tsuki-wscp.
We have used some of these posts to build our list of alternatives
and similar projects.
-
[P] I created a web scraper for AI/ML training.
The github repo with documentation: https://github.com/Tsujimar/tsuki-wscp
- I created a web scraper for AI/ML training
What are some alternatives?
When comparing ML_twitter_celebs and tsuki-wscp you can also consider the following projects:
svm-pytorch - Linear SVM with PyTorch
Encord Active - Open source active learning toolkit to find failure modes in your computer vision models, prioritize data to label next, and drive data curation to improve model performance.