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PySyft

A library for encrypted, privacy preserving machine learning
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What is PySyft?

It is a Python library for secure and private Deep Learning. PySyft decouples private data from model training, using Federated Learning, Differential Privacy, and Multi-Party Computation (MPC) within the main Deep Learning frameworks like PyTorch and TensorFlow.
PySyft is a tool in the Machine Learning Tools category of a tech stack.
PySyft is an open source tool with 5.9K GitHub stars and 1.3K GitHub forks. Here’s a link to PySyft's open source repository on GitHub

Who uses PySyft?

PySyft Integrations

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PySyft's Features

  • Secure and private Deep Learning
  • Decouples private data from model training

PySyft Alternatives & Comparisons

What are some alternatives to PySyft?
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
See all alternatives

PySyft's Followers
10 developers follow PySyft to keep up with related blogs and decisions.
Павел Бондаренко
Nathan e
Paritosh Tyagi
주현 강
comy cosmin
programminghumanity
Annie D
Dheeraj  Pai
Meixu Song
Raphael Zulliger