Differential-Privacy-Guide
gretel-python-client
| Differential-Privacy-Guide | gretel-python-client | |
|---|---|---|
| 1 | 3 | |
| 13 | 43 | |
| - | - | |
| 2.6 | 9.1 | |
| over 2 years ago | about 24 hours ago | |
| Python | Python | |
| - | Apache License 2.0 |
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.
Differential-Privacy-Guide
gretel-python-client
What are some alternatives?
adversarial-robustness-toolbox - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
SDV - Synthetic data generation for tabular data
tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow
gretel-synthetics - Synthetic data generators for structured and unstructured text, featuring differentially private learning.
ReTube - ReImagine Tubing
Copulas - A library to model multivariate data using copulas.
privacy - Library for training machine learning models with privacy for training data
ydata-synthetic - Synthetic data generators for tabular and time-series data
isp-data-pollution - ISP Data Pollution to Protect Private Browsing History with Obfuscation
Mimesis - Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.