OpenMined/PySyft-TensorFlow

SOON TO BE DEPRECATED - The TensorFlow bindings for PySyft

Language: Python - Size: 119 KB - Last synced at: 6 days ago - Pushed at: almost 5 years ago - Stars: 57 - Forks: 11

mkucz95/encrypted_ai_finance

Credit Approval Classification Deep Learning Model using Differential Drivacy, Secure Multi-Party Computation, and Federated Learning

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abbas5253/SplitNN-for-Vertically-Partitioned-Data

Integration of SplitNN for vertically partitioned data with OpenMined's PySyft

Language: Jupyter Notebook - Size: 22.5 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 19 - Forks: 8

sisinflab/recsys2021-pursuing-privacy

Material supporting the tutorial "Pursuing Privacy in Recommender Systems: The View of Users and Researchers from Regulations to Applications" held at the 15th ACM Conference on Recommender Systems in Amsterdam, Netherlands

Language: Jupyter Notebook - Size: 22.5 MB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 18 - Forks: 4

vermasrijan/srijan-gsoc-2020

Healthcare-Researcher-Connector Package: Federated Learning tool for bridging the gap between Healthcare providers and researchers

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vivekkhimani/federated_learning_pysyft

A simple federated learning implementation on MNIST dataset using PySyft. Main goal of the project was to get used to the PySyft federated learning functionality instead of using traditional PyTorch features.

Language: Python - Size: 8.79 KB - Last synced at: 18 days ago - Pushed at: about 1 year ago - Stars: 13 - Forks: 0

ashwindasr/Federated-Learning

An implementation of Federated Learning using Pytorch and PySyft

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souravs17031999/Federatedencryption-showcase

The project showcasing federated learning of model and testing on encrypted data and model

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tayebiarasteh/federated_he

Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with privacy guarantees.

Language: Python - Size: 585 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 7 - Forks: 0

arghyadeep99/Federated-Learning-for-Hospital-Data-Distributed-Computing

Demonstration of application of Distributed Computing in Federated Learning for our Semester-8 Course on Distributed and Cloud Computing

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Fustincho/UD-Private-In-bed-Posture-Classification

Project entry for the Secure and Private AI Challenge, hosted by Udacity and sponsored by Facebook (May - August, 2019)

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GOVINDDIXIT/SMS-Spam-Detection

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souravs17031999/SmogDetection

Repo for project : smog detection project at Udacity Project Showcase

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tayebiarasteh/privacydomain

Securing Collaborative Medical AI by Using Differential Privacy

Language: Python - Size: 123 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

DeepHiveMind/Federated-Learning_simplified

:fire: Federated Learning Simplified with Frameworks

Size: 124 KB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

etesami/MOE-FL

The implementation of the "Robust Federated Learning by Mixture of Experts" study.

Language: Python - Size: 20.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 1

Suhanip/Federated-Learning

Language: Jupyter Notebook - Size: 877 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 3

decentralizedautomata/Research_Papers

A collection of research and survey papers of differential privacy and federated learning

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souravs17031999/60days-of-udacity

Repo including all the daily updates of #60daysofudacity Udacity Challenge

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sourcecode369/secured-and-private-ai

Implementations notebooks and scripts of secured and private ai scholarship challenge from facebook.

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masoodkhanpatel/60DaysOfUdacity

The premise of this challenge is to build a habit of practicing new skills by making a public commitment of practicing the topics of Secure and Private AI program every day for 60 days.

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kshntn/SPAIC

Secure and Private AI Scholarship Challenge Udacity

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youben11/udacity-secure-private-ai

The workspace for the Secure and Private AI course on Udacity. https://www.udacity.com/course/secure-and-private-ai--ud185

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Berenice2018/DeepLearning

Udacity Deep Learning, PyTorch, PySyft

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snehilsanyal/federated-recipes

🌻🌐 A repository that contains Federated Learning Recipes.

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bavba/Multi-party_computation_for_financial_data_analysis

Multi-Party Computation transforms data handling by decentralizing trust among multiple participants. This ensures that no single entity demands absolute trust. An advantage for companies in safeguarding data privacy: once data leaves the user's computer, it remains obscured from any single external entity.

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abdelino17/secure-private-ai

Secure & Private AI Challenge Codes

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