Design a federated learning system in seven steps

What should you consider when building an enterprise federated learning system?Photo by Hunter Harritt on UnsplashIntroductionCompanies like
Federated Learning 2 years ago

Encrypted Inference using ResNet-18

Encrypted inference with ResNet-18 using PyTorch + PySyft on ants & bees images
Private ML 4 years ago

CrypTen Integration into PySyft

CrypTen integrated in PySyft: a fast SMPC backend for secure computation between servers.
Multi-Party Computation 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

What is Secure Multi-Party Computation?

This post is part of our Privacy-Preserving Data Science, Explained Simply series.
Multi-Party Computation 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

Towards privacy with RStudio: Encrypted deep learning with Syft and Keras

In this post, we introduce Syft, an open-source framework that integrates with PyTorch as well as TensorFlow, and show how to use it from R. In an example use case, we obtain private predictions from an R Keras model.
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

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

Encrypted Training with PyTorch + PySyft

Encrypted Training of Deep Learning models with PyTorch + PySyft on MNIST
Private ML 5 years ago

Encrypted Deep Learning Classification with PyTorch & PySyft

Encrypted Deep Learning Classification with PyTorch & PySyft in < 33ms on MNIST
Private ML 5 years ago