How-to Guides

Syft is OpenMined’s open source stack that provides secure and private Data Science in Python. Syft decouples private data from model training, using techniques like Federated Learning, Differential Privacy, and Encrypted Computation. This is done with a numpy-like interface and integration with Deep Learning frameworks, so that you as a Data Scientist can maintain your current workflow while using these new privacy-enhancing techniques.



TIP: To run all the tutorials interactively in Jupyter Lab on your own machine, type:

pip install -U hagrid
hagrid quickstart

Once you have the installation completed, the best place to start is by identifying your role.

A. Getting Started with Data Owner 👨🏻‍💼

Data Owners provide datasets which they would like to make available for study by an outside party they may or may not fully trust has good intentions.

You Will Learn ⬇️

B. Getting Started with Data Scientist 👩🏽‍🔬

Data Scientist’s are end users who desire to perform computations or answer a specific question using one or more data owners’ datasets.

You Will Learn ⬇️

Part 7: Connect to a Domain
Part 8: Searching for Datasets on the Domain
Part 9: Exploring a Dataset in the Domain
Part 10: Training a Model
Part 11: Retrieving Secure Results