privacy
Library for training machine learning models with privacy for training data (by tensorflow)
dp-xgboost
By sarus-tech
| privacy | dp-xgboost | |
|---|---|---|
| 2 | 6 | |
| 1,874 | 22 | |
| 0.7% | - | |
| 7.8 | 6.6 | |
| 7 days 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.
privacy
Posts with mentions or reviews of privacy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-17.
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 privacy and dp-xgboost you can also consider the following projects:
differential-privacy - Google's differential privacy libraries.
tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow
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.
EnvisEdge - Deploy recommendation engines with Edge Computing
Differential-Privacy-Guide - Differential Privacy Guide
adversarial-robustness-toolbox - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams