nowfound

Life & fun · October 23, 2018

Encrypted Deep Learning in PyTorch

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

Encrypted Deep Learning in PyTorch launched on October 23, 2018 with 37 votes, #910 of 2,827 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 7 years on.

In plain words

Encrypted Deep Learning in PyTorch is a tool that enables machine learning model training and inference while keeping data encrypted. It integrates with PyTorch, a popular deep learning framework, allowing developers to work with sensitive information without exposing it in plain text. The software is designed for researchers and engineers who need to perform neural network computations on confidential data while maintaining privacy. The project is hosted on GitHub as an open-source resource.

written from the facts on this page · September 2026

Does a similar job

all alternatives →
  • Encrypted Deep Learning Classification with PyTorch and PySyft2019 · blog.openmined.org · ▲10

    Update as of November 18, 2021: The version of PySyft mentioned in this post has been deprecated. Any implementations using this older version of PySyft are…

  • PyTorch Lightning2020 · pytorchlightning.ai · ▲79

    The light PyTorch wrapper for high-performance AI research

  • TorchGAN – Research Framework for Modelling GANs Based on Pytorch2018 · github.com · ▲56

    Research Framework for easy and efficient training of GANs based on Pytorch - torchgan/torchgan

  • Weights & Biases2019 · wandb.ai · ▲110

    Developer tools for deep learning & machine learning

  • Graphlearn-for-PyTorch, distributed graph learning on PyTorch2023 · github.com · ▲9

    Hello HN, We are pleased to introduce you graphlearn-for-pytorch (https://github.com/alibaba/graphlearn-for-pytorch), an open-source distributed graph neural network library based on PyTorch and compatible with PyG. Our library is designed to make it easy for developers to build and train large-scale graph models in a distributed environment. With graphlearn-for-pytorch, you can leverage GPUs to accelerate graph sampling and utilize UVA to reduce the overheads of feature collection. Following a scalable design, graphlearn-for-pytorch supports training GNN models on…

More life & fun this month

the category →

Source: Show HN post ↗

Launched alongside, October 2018

the whole month →
  • Funkify▲1,004

    Experience the web through the eyes of the differently abled

    Life & fun · 2018

  • Neil Patel's free keyword research tool

    Growth · 2018 · neilpatel.com

  • Cruip▲696

    Free and premium landing page templates for startups

    Growth · 2018 · cruip.com

  • Automate your workflow from idea to production

    Dev tools · 2018 · github.com

  • Example of bloated website in 2018

    Life & fun · 2018 · 2018.bloomca.me

  • Discover new, productive Notion templates

    Work · 2018 · notionpages.com