DPL
SDGym
DPL | SDGym | |
---|---|---|
1 | 1 | |
12 | 243 | |
- | 1.6% | |
5.6 | 7.8 | |
6 months ago | 9 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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DPL
SDGym
-
[D] Synthetic data generation techniques for data privacy
I would suggest starting with "differentially private synthetic data generation". These methods utilize differential privacy and mostly protect against membership inference attacks, are very popular in the ML/DL community. I would also suggest reading up on privacy preserving ML methods in general and adversarial attacks against them (membership inference, inversion, reconstruction, property inference), but if you're keen on reading some code, check out sd-gym: https://github.com/sdv-dev/SDGym. The authors have collected implementations for a lot of PPSDG methods. Also I strongly suggest reading McMahan's 2016 paper: https://arxiv.org/abs/1607.00133.
What are some alternatives?
prompttools - Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).
Mimesis - Mimesis is a robust data generator for Python that can produce a wide range of fake data in multiple languages.
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
SDV - Synthetic data generation for tabular data
tapnet - Tracking Any Point (TAP)
Copulas - A library to model multivariate data using copulas.
autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data [Moved to: https://github.com/autogluon/autogluon]
FAST-RIR - This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
AgileRL - Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.