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Welcome to Antigranular's Documentation
Here you will find comprehensive information and guides on how to effectively use Antigranular, a powerful tool for granular data analysis. Delve into our detailed problem scopes and scoring metrics to understand the various types of problems you will work on and how they are assessed on the platform.
Explore our notebooks to gain insights from practical examples of differentially private libraries and apply Antigranular to your own projects. Additionally, there are some must read quick guides to accelerate your mastery of eyes-off data science. Get ready to unlock the full potential of differentially private data analysis with Antigranular!
Quickstart Guides
Antigranular is a community-driven, open-source platform that merges confidential computing and differential privacy. This creates a secure environment for handling and unlocking the full potential of unseen data. Learn more about the platform using the quick guides below.
Private Python, End to End Data Analysis
Private Python is a specialised version of the Python programming language that offers a user-friendly and accessible coding environment. It is specifically designed for working with differentially private data, ensuring privacy protections are embedded at every step.
Private Python
By combining the power of pure functions, restricted imports, and type safety, Private Python provides a reliable and secure development experience.
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The Packages
Supported Packages in Private Python
Core Concepts
Discover Core concepts of Antigranular and start the privacy journey.
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Differential Privacy
Differential privacy is a privacy-preserving concept that ensures the protection of sensitive data in data science and machine learning. By introducing controlled noise to computations, it prevents the disclosure of specific information about individuals, allowing organisations to leverage data while maintaining individuals' privacy and building trust.
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Trusted Execution Environments
Confidential Computing, synonymous with the terms "Trusted Execution Environment" (TEE) or "Secure Enclave", represents a significant leap in data security and privacy. It is a concept that is pushing the boundaries of what is possible in data protection, especially in the realm of cloud computing.
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