Sarus Technologies

Sarus Technologies's repositories

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.

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dp-xgboost

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demo-notebooks

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gallimimus

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differential-privacy

Google's differential privacy libraries.

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fast-differential-privacy

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sarus-tech.github.io

DP compilation presentation

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privacybuckets

A implementation of Privacy Buckets: A numerical tool to calculate privacy loss

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private-statistics

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smartnoise-core

Differential privacy validator and runtime

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smartnoise-sdk

Tools and service for differentially private processing of tabular and relational data

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xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

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azure-sandbox

Code to install Sarus on Azure

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opendp

The core library of differential privacy algorithms powering the OpenDP Project.

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