Highlights
Stars
Mega list of 1 on 1 meeting questions compiled from a variety to sources
A collection of Google research projects related to Federated Learning and Federated Analytics.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Training PyTorch models with differential privacy
Site of W3C Workshop on Web & Machine Learning
Privacy transformations on Spark and Pandas dataframes backed by a simple policy language.
list of differential-privacy related resources
Summary of the book The Pragmatic Programmer by Andrew Hunt and David Thomas
The fastai book, published as Jupyter Notebooks
π Learning Kotlin Coroutines and Flows for Android by example. π Sample implementations for real-world Android use cases. π Unit tests included!
Source code listings and exercises for Functional Programming in Kotlin
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
A curated list of resources dedicated to federated learning.
A privacy-preserving app for comparing last-known locations of coronavirus patients
Library for training machine learning models with privacy for training data
A repo for exploring the use of Hyperledger Aries to facilitate decentralised identity services.
Proof of concept on a predictive maintenance use case using federated learning to continuously improve predictions of the remaining lifetime of aircraft gas turbine engines.
Code accompanying the paper "A Generative Framework for Zero Shot Learning with Adversarial Domain Adaptation"
A library for doing homomorphic encryption operations on tensors
The official Syft worker for iOS, built in Swift
Defines types for all Serde encoding across languages
The official Syft worker for Web and Node, built in Javascript
A multi-language library for translating commands between PyTorch, TensorFlow, and TensorFlow.js
Kotlin Code Generator and Runtime for Protocol Buffers