Padawan Program Alumni

OpenMined's Padawan Program continues to grow and support a diverse group of learners. We recognize our Padawan Program Alumni, acknowledge
PySyft 2 years ago

OpenMined's R2Q4 Padawan Program Graduates

Congratulations to all of our R2Q4 Padawan Program Graduates!
Announcements 2 years ago

CKKS explained, Part 5: Rescaling

Fifth part of the series CKKS explained where we see how to define rescaling
Homomorphic Encryption 4 years ago

CKKS explained, Part 4: Multiplication and Relinearization

Fourth part of the series CKKS explained where we see how to define ciphertext multiplication and relinearization
Homomorphic Encryption 4 years ago

How to setup PySyft on Windows 10

In this tutorial, you are going to learn how to setup PySyft, a privacy-preserving machine learning framework, on Windows 10.
Deep Learning 4 years ago

CKKS explained, Part 3: Encryption and Decryption

Third part of the series CKKS explained where we see how to build an HE system from RLWE, implement encryption, decryption, addition and multiplication.
Homomorphic Encryption 4 years ago

CKKS explained, Part 2: Full Encoding and Decoding

Second part of the series CKKS explained where we see how to implement CKKS encoder and decoder.
Homomorphic Encryption 4 years ago

CKKS explained: Part 1, Vanilla Encoding and Decoding

First part of the series CKKS explained where we see how to implement a vanilla encoder and decoder.
Homomorphic Encryption 4 years ago

Announcing 4 New Libraries for Federated Learning on Web and Mobile Devices

As part of the PyTorch/OpenMined grants we announced last December, the Web & Mobile team has been hard at work on developing 4 new libraries for model-centric federated learning.
Announcements 4 years ago

Announcing the OpenMined-UCSF Data-Centric 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 grants will focus on bringing data-centric federated learning with differential privacy budgeting to PyGrid.
Announcements 4 years ago

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.
Use Cases 4 years ago

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.
Federated Learning 4 years ago

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.
Private ML 4 years ago

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
Federated Learning 4 years ago

Introduction to Federated Learning and Privacy Preservation using PySyft and PyTorch

Federated Learning and Additive Secret Sharing using the PySyft framework
Deep Learning 4 years ago

Split Neural Networks on PySyft and PyTorch

Update as of November 18, 2021: The version of PySyft mentioned in this post has been deprecated. Any implementations using this older versi
Private ML 4 years ago

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.
Federated Learning 5 years ago

Asynchronous Federated Learning in PySyft

Update as of November 18, 2021: The version of PySyft mentioned in this post has been deprecated. Any implementations using this older versi
Federated Learning 5 years ago

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.
Deep Learning 5 years ago

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.
Federated Learning 5 years ago

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

Deep Learning -> Federated Learning in 10 Lines of PyTorch + PySyft
Federated Learning 5 years ago