Announcing the OpenMined-UCSF Dynamic Federated Learning Fellowship

We’re very excited to announce the next round of open-source software development grants in the OpenMined community, generously sponsored by the University of California San Francisco! These fellowships will focus on bringing dynamic federated learning with differential privacy budgeting to PyGrid.

Sentiment Analysis on Multiple Datasets With SyferText - Demo

How can you do pre-processing if you are not allowed to have access to plaintext data? SyferText can help you! With SyferText, you can define pre-processing components to perform pre-processing remotely, blindly and in a completely secure fashion.

Federated Learning for Credit Scoring

Want bureaus to score your credit without hoarding your data? Find out how FL can enable privacy-preserving, cross-border credit assessment.

Privacy-Preserving Data Science, Explained

In this blog series, we’ll explain common topics in privacy-preserving data science, from a single sentence to code examples. We hope these posts serve as a useful resource for you to figure out the best techniques for your organization.

Predictive Maintenance of Turbofan Engines using Federated Learning with PySyft and PyGrid

Is it possible to benefit from the wonders of machine learning without having direct access to data? Today, machine learning can be used to

Introduction to Federated Learning and Privacy Preservation using PySyft and PyTorch

Federated Learning and Additive Secret Sharing using the PySyft framework

Split Neural Networks on PySyft and PyTorch

Summary: In this blog we are going to provide an introduction into a new decentralised learning methodology called, ‘Split Neural Networks’.

Announcing the OpenMined-PyTorch Federated Learning Fellowships

We’re very excited to announce the next round of grants sponsored by the PyTorch team! This grant will focus on developing “worker libraries”, allowing PySyft code to be executed in other environments like a mobile phone or web browser.

Asynchronous Federated Learning in PySyft

In this post, we provide a showcase of applying federated learning using PySyft. PySyft is an open source python library for secure and priv

Privacy-Preserving AI in Medical Imaging: Federated Learning, Differential Privacy, and Encrypted Computation

In medical imaging, necessary privacy concerns limit us from fully maximizing the benefits of AI in our research. These modern privacy techniques could allow us to train our models on encrypted data from multiple institutions, hospitals, and clinics without sharing the patient data.

Federated Learning of a Recurrent Neural Network on Raspberry PIs

In this article, you are going to learn how to setup PySyft on a Raspberry PI and how to train a Recurrent Neural Network in a federated way.

Deep Learning -> Federated Learning in 10 Lines of PyTorch + PySyft

Deep Learning -> Federated Learning in 10 Lines of PyTorch + PySyft