tf2-published-models
Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard. (by sarus-tech)
dp-xgboost
By sarus-tech
tf2-published-models | dp-xgboost | |
---|---|---|
1 | 6 | |
38 | 22 | |
- | - | |
0.0 | 6.6 | |
over 2 years ago | 4 months ago | |
Python | C++ | |
Apache License 2.0 | 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.
tf2-published-models
Posts with mentions or reviews of tf2-published-models.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-17.
-
Launch HN: Sarus (YC W22) – Work on sensitive data with differential privacy
- https://github.com/sarus-tech/tf2-published-models
We plan to continue building trust in the tools we are using by publishing some of them.
dp-xgboost
Posts with mentions or reviews of dp-xgboost.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-17.
- Launch HN: Sarus (YC W22) – Work on sensitive data with differential privacy
- Show HN: DP-XGBoost, scalable ML with differential privacy
-
DP-XGBoost: Private Machine Learning at Scale
The source code is there: https://github.com/sarus-tech/dp-xgboost
- DP-XGBoost – Scalable ML with differential privacy
What are some alternatives?
When comparing tf2-published-models and dp-xgboost you can also consider the following projects:
differential-privacy - Google's differential privacy libraries.
GLOM-TensorFlow - An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
privacy - Library for training machine learning models with privacy for training data