Skip to main content

First Steps

1
Login to Antigranular

Head over to Antigranular ↗ and click the top right button to login (or register) with your email, GitHub or Google.

2
Connect through Colab or Jupyter and start coding

Open the Getting Started Notebook ↗ and follow the steps to connect to our platform and run your code in our enclaves!

3
Learn more

Explore the following API References, Guides and Core Concepts to learn more!

Guides

Working with Antigranular

The AG Python client and Jupyter extension can bring your script to life in a secure environment by using a specialised version of Python created by AG This Python version operates under restricted conditions, allowing only methods that guarantee differential privacy.

Read More

Using Private Pandas

AG provides a differentially private version of the pandas library, which lets users handle private data frames and series and perform various statistical analyses with differential privacy guarantees.

Read More

Using Private TensorFlow

TensorFlow Privacy is a Python library developed by Google that enables training of machine learning models with privacy guarantees, in particular through the implementation of differential privacy.

Read More

Using Private Opacus

Opacus is a library enabling differentially private training of PyTorch models. By adjusting the model's training process, Opacus ensures the model's outputs do not disclose individual data points from the training set.

Read More

Concepts

API References

Pandas API

op_pandas is AG's implementation of the Pandas library. The op_pandas library allows you to import datasets and handle their data efficiently and privately.

Read More

Diffprivlib API

The Diffprivlib library implements differential privacy techniques for various data analysis tasks. It can be viewed as a differentialy private version of scikit-learn, implementing the DP-equivalents of many of the sklearn models.

Read More

OpenDP API

OpenDP is a powerful library for privacy-preserving data analysis. It provides a wide range of functions and methods to ensure the privacy of sensitive data while enabling a meaningful analysis.

Read More

SmartNoise Synth API

SmartNoise-Synth is part of SmartNoise SDK and is built on OpenDP. It offers multiple differentially private synthesizers.

Read More

Help and Support

Contact support