openfl VS tf-encrypted

Compare openfl vs tf-encrypted and see what are their differences.

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openfl tf-encrypted
9 2
1,855 1,192
0.8% 0.5%
8.7 0.0
6 days ago 7 months ago
Haxe Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

openfl

Posts with mentions or reviews of openfl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-21.

tf-encrypted

Posts with mentions or reviews of tf-encrypted. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing openfl and tf-encrypted you can also consider the following projects:

Kha - Ultra-portable, high performance, open source multimedia framework.

stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

heaps - Heaps : Haxe Game Framework

horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. [Moved to: https://github.com/horovod/horovod]

PySyft - Perform data science on data that remains in someone else's server

Differential-Privacy-Guide - Differential Privacy Guide

FATE - An Industrial Grade Federated Learning Framework

openfl - An open framework for Federated Learning.

armory - 3D Engine with Blender Integration

privacy - Library for training machine learning models with privacy for training data

flixel - Free, cross-platform 2D game engine powered by Haxe and OpenFL

mia - A library for running membership inference attacks against ML models